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absa_bca_v2

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@bukopinsiaga nasabah dipersulit untuk tutup CC padahal enggak ada transaksi cuma biaya tahunan .

<product-kartu kredit>dipersulit tutup CC</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

DANAMON enggak konsisten .Ditawarkan CC Platinum , konfirmasi Telepon OKE Platinum , eh yang diterima CC Gold , konfirmasi tutup saja deh @kartudanamon

<general>enggak konsisten . Ditawarkan CC Platinum , konfirmasi Telepon OKE Platinum , eh yang diterima CC Gold , konfirmasi tutup saja deh</general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

saya keberatan dan minta tutup CC bukopin - nya tetapi dipersulit oleh CS @bukopinsiaga tolong @YLKI_ID @bank_indonesia @ojkindonesia

<product-kartu kredit>tutup CC dipersulit oleh CS</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

dan pelayanan kurir @danamon yang kurang ajar mengatakan rumah saya tutup , padahal rumah saya enggak tutup , sehingga cc saya balik ke pusat

<service-general>kurir kurang ajar</service-general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@MaybankID stop menawarkan isi pulsalah , tiap hari telepon-telepon CS - nya sangat mengganggu .saya segera tutup CC maybank .ini bank apa konter pulsa !

<service-customer center>stop menawarkan isi pulsalah , tiap hari telepon-telepon CS - nya sangat mengganggu</service-customer center>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

sejak dialihkan maybank malah makin mahal .ogah banget deh !Sebentar lagi mau gue tutup saja itu CC !

<product-kartu kredit>makin mahal CC</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

pakai CC BII banyak promo nya kayak nya gue bakal tutup si city ; p

<product-kartu kredit>CC banyak promo</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Kalau boleh tulis status : Jangan kredit di BII , proses ribet , susah , dan lama .Benaran deh aku publikasikan .

<product-kartu kredit>kredit proses ribet , susah , dan lama</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

ribet benar ini cc bank mega , enggak bisa bayar antarbank , jatuh nya kliring ,

<product-kartu kredit>ribet benar cc enggak bisa bayar antarbank</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

si CC bii ribet juga bayar satu-satu kartu nya

<product-kartu kredit>CC ribet juga bayar satu-satu kartu nya</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

enakan si CC bca gampang enggak ribet !

<product-kartu-kredit>enakan gampang enggak ribet</product-kartu-kredit> <product-kartu kredit>CC</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

BumiPutra CC : aktivasi CC Ribet , tutup CC Ribet juga .

<product-kartu kredit>CC aktivasi Ribet tutup Ribet</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Boleh nih CC BII tanpa syarat-syarat ribet

<product-kartu kredit>CC</product-kartu kredit> <product-kartu-kredit>tanpa syarat-syarat ribet</product-kartu-kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Ampun deh sama bii , sudah risiko ribet sekarang pemeliharaan jaringan melulu .Setor tunai saldo enggak bertambah , padahal Mau bayar tagihan cc

<facility-e-channel>ribet sekarang pemeliharaan jaringan melulu Setor tunai saldo enggak bertambah</facility-e-channel>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@danamon kartu cc saya lama sekali pengiriman .batal saja deh .Ribet banget belum juga saya gunakan !telepon @HelloDanamon berkali-kali dengan cs yang kurang kompeten .

<product-kartu kredit>cc lama sekali pengiriman Ribet banget belum juga saya gunakan</product-kartu kredit> <service-customer center>telepon HelloDanamon berkali-kali dengan cs yang kurang kompeten</service-customer center>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@danamon kenapa saya dikirimi cc baru lagi !Enggak pernah meminta tambah cc .Cc yang ada saja ke biaya tahunan , penghapusan nya bersyarat , ribet .

<product-kartu kredit>Cc biaya tahunan penghapusan nya bersyarat ribet</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@GibsonLie @kartudanamon CC danamon itu ribet ya !

<product-kartu kredit>CC ribet</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Mau omong sama operator cc - nya danamon saja susah nya ampun-ampun .Ribet amat ya proses nya .

<product-kartu kredit>omong sama operator cc susah nya ampun-ampun Ribet amat proses nya</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Saya pengguna baru cc danamaon saya sudah sering komplain ke hello danamon dari nomor telepon genggam saya sudah susah masuk nya @HelloDanamon

<service-customer center>komplain hello danamon susah masuk nya</service-customer center>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@kartudanamon admin susah sekali ya tanya status aplikasi cc danamon

<product-kartu kredit>susah sekali tanya status aplikasi cc</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@kartudanamon ah susah sekali mendapatkan cc danamon .

<product-kartu kredit>susah sekali mendapatkan cc</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

menyesal juga menurunkan pagu kredit cc permata .Menaikkan lagi nya susah .

<product-kartu kredit>pagu kredit cc Menaikkan lagi nya susah</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Karena kebiasaan pakai Permata Mobile .Mau bayar cc pakai m - BCA berasa ribet dan enggak nyaman !Bagaimana saya cinta Permata mobile !

<facility-m-bca>bayar cc m - BCA ribet dan enggak nyaman</facility-m-bca> <facility-aplikasi>saya cinta Permata mobile</facility-aplikasi>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Menyesal buka cc permata bank kalau tahu ribet kayak begini , mengajukan CC saja enggak begini amat perasaan

<product-kartu kredit>buka cc ribet kayak begini</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Untuk syarat mengajukan CC Permata Bank Shopping Card hanya dengan fotokopi KTP & fotokopi CC bank lain yang sudah aktif 1 tahun .mudah & enggak ribet :)

<product-kartu kredit>syarat mengajukan CC mudah & enggak ribet</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

enak ya BCA prioritas langsung tidak perlu antre .ah menyesal dikasih pindah prioritas tidak mau

<service-prioritas>enak prioritas langsung tidak perlu antre</service-prioritas>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

BCA prioritas kosong enak banget hahaha

<service-prioritas>prioritas kosong enak banget</service-prioritas>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Memang enak kalau punya kartu prioritas BCA : p

<service-prioritas>enak kartu prioritas</service-prioritas>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

gila ya tutup kartu kredit @CC_OCBCNISP @ocbcnisp @ocbcnisp susah banget padahal sudah lunas .Enggak lagi deh pakai CC ocbcnisp #ocbcnisp

<product-kartu kredit>tutup kartu kredit susah banget padahal sudah lunas</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@CC_OCBCNISP kayak nya susah dapat cc - nya ocbc nisp padahal kita nasabah .Sudah pernah mengajukan tetapi ditolak .

<product-kartu kredit>susah dapat cc mengajukan ditolak</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Parah , mau tutup cc ocbc nisp saja ribet benar , dari tanggal 28 Februari 2012 kemarin , dibilang 3 hari kerja , hari ini gue telepon lagi , 3 hari kerja lagi .ck

<product-kartu kredit>tutup cc ribet benar</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@CC_OCBCNISP layanan anda sangat buruk !Minta hapus biaya tahunan 2 bulan enggak tuntas-tuntas juga , mau menutup kartu jadi enggak bisa .Payah !

<product-kartu kredit>layanan anda sangat buruk hapus biaya tahunan 2 bulan enggak tuntas-tuntas menutup kartu enggak bisa</product-kartu kredit> <general>Payah</general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Kata nya ada promo cc ocbc nisp , ternyata enggak ada .Payah nih ocbc

<product-kartu kredit>promo cc enggak ada . Payah nih</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@CC_OCBCNISP aku saja nasabah ocbc nisp , aplikasi aku ditolak .payah ocbc .

<product-kartu kredit>aplikasi ditolak</product-kartu kredit> <general>payah</general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

tolong dicek , saya pakai fasilitas bca mana pun , memuat nya agak lama , eh akhirnya malah dinyatakan gagal .

<facility-e-channel>fasilitas memuat nya agak lama , eh akhirnya malah dinyatakan gagal</facility-e-channel>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA Saya mencoba mengakses menu m - BCA saya , namun saya mendapat respons " Fasilitas Mobile Banking terblokir " .bagimana sih padahal saya baru coba akses lo

<facility-m-bca>mengakses menu m - BCA mendapat respons sub-facility-m-bca-neg[209] _ _ 90-17 10633-10642 Fasilitas sub-facility-m-bca-neg[209] _ _ 90-18 10643-10649 Mobile sub-facility-m-bca-neg[209] _ _ 90-19 10650-10657 Banking sub-facility-m-bca-neg[209] _ _ 90-20 10658-10667 terblokir sub-facility-m-bca-neg[209] _ _ 90-21 10668-10669 . bagimana sih padahal saya baru coba akses</facility-m-bca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

saya punya 2 rekening bca dan kedua nya menggunakan klikbca .saya terbantu dengan potongan bulanan yang enggak sama tanggal nya

<facility-klikbca>klikbca terbantu dengan potongan bulanan yang enggak sama tanggal nya</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA kurang kekinian nih mending ada fasilitas dari BCA jika transaksi debit atau kredit yang dikasih tahu lewat whatsapp secara otomatis

<general>kurang kekinian</general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Dahulu saya pakai bca karena ada m - banking .Sekarang semua bank pemerintah sudah ada fasilitas ini jadi pindah ke bank milik negara saja

<facility-m-bca>ada m - banking</facility-m-bca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

layanan e - SAMSAT harus nya menggunakan fasilitas ATM dari BCA saja biar lebih gampang

<facility-atm>ATM lebih gampang</facility-atm>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Nomor telepon genggam yang terhubung dengan fasilitas sms bca saya adalah sim 2 dan nomor tersebut memiliki cukup pulsa .tetapi ini transaksi saya dari tadi gagal melulu lo

<facility-m-bca>sms transaksi gagal melulu</facility-m-bca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Kalau saya lebih suka BCA xpresi selain biaya admin sedikit .Ada fasilitas e - banking , mobile banking terus bisa tarik tunai & setor di mana-mana .Admin murah

<product-simpanan>lebih suka xpresi biaya admin sedikit Admin murah</product-simpanan> <facility-e-channel>Ada e - banking , mobile banking</facility-e-channel> <facility-atm>bisa tarik tunai & setor di mana-mana</facility-atm>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

tiap gue pakai m - bca selalu enggak bisa deh padahal mah enggak ada masalah apa-apa dari perangkat gue .

<facility-m-bca>m - bca selalu enggak bisa</facility-m-bca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

bca atau mandiri .gampang .mudah .fasilitas enak .beuh top markotop

<general>gampang . mudah . fasilitas enak . beuh top markotop</general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA .halo !harus nya fasilitas klikBCA bisa transfer daring Bersama / Prima .Susah banget kalau harus ke atm / kalau m - banking eror

<service-general>Servis bagus banget</service-general> <facility-general>Fasilitas cukup lengkap</facility-general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@XpresiBCA seneng banget bisa pakai fasilitas bca

<product-simpanan>XpresiBCA seneng banget</product-simpanan>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA @KartuKreditBCA puas banget dengan pelayanan BCA , pekerjaan menjadi lebih mudah , fasilitas internet , atm , cs , telepon selular , semuanya oke : - )

<service-general>puas banget pelayanan pekerjaan menjadi lebih mudah</service-general> <facility-klikbca>fasilitas internet oke</facility-klikbca> <facility-atm>atm oke</facility-atm> <service-cs>cs oke</service-cs> <service-haloBCA>telepon selular oke</service-haloBCA>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Ternyata BCA bsd ini adalah proyek percontohan .pantas saja bagus begitu fasilitas & servis nya

<service-general>bagus begitu servis</service-general> <facility-general>bagus begitu fasilitas</facility-general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Bank BCA kata nya Bank dengan nasabah terbanyak , tetapi fasilitas atm - nya enggak banget deh .banyak yang rusak dan enggak selalu ada tersedia di mal besar !

<general>Bank dengan nasabah terbanyak</general> <facility-atm>atm enggak banget deh . banyak yang rusak dan enggak selalu ada tersedia di mal besar</facility-atm>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Tanggung banget menyediakann fasilitas layanan Tunai BCA di kasir Indomaret .bisa nya cuma 100 ribu tetapi saya mau nya 1 juta huh

<facility-general>Tanggung banget fasilitas layanan Tunai bisa nya cuma 100 ribu tetapi saya mau nya 1 juta</facility-general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

di PVJ sediakan atm BCA dong .masa segede itu enggak ada atm bca nya

<facility-atm>enggak ada atm</facility-atm>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@BNI46 tolong perbaiki fasilitas dong .hasil transfer ke BCA dari pagi 31 - 12 - 2013 kok enggak masuk-masuk .mengecewakan sekali

<facility-e-channel>transfer enggak masuk-masuk . mengecewakan sekali</facility-e-channel>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Masih zaman ?Pakai BCA BY PHONE dong biar enggak perlu mengecek fasilitas e - banking dahulu

<facility-m-bca>m - banking gagal terus sistem daring nya sejak kemarin rusak . kasihan nasabah dong</facility-m-bca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@BNI46 bikin fasilitas setoran tunai dong kayak bank BCA .gue kan enggak ada waktu ke bank .kan enak itu .lo untung dapat duit gue .gue minta fasilitas .

<facility-keybca>KeyBCA tombol keras banget</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

5 Tahun ini jadi boros , apa-apa transfer pakai keybca

<facility-keybca>boros transfer keybca</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

sisi baiknya ya keybca lebih memudahkan banget buat toko daring , terutama gue yang pekerjaan nya men - dropship barang .

<facility-keybca>keybca lebih memudahkan banget buat toko daring</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA ini key BCA kenapa sih Susah banget buat transfer

<facility-keybca>key BCA Susah banget transfer</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Di tengah transaksi tiba2 keybca tidak dapat digunakan , muncul tulisan tombol dan mati

<facility-keybca>keybca tidak dapat digunakan , muncul tulisan tombol dan mati</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

saya tidak menemukan informasi yang menyatakan bahwa keybca akan tidak sinkron jika tidak digunakan selama lebih dari 3 bulan .coba dong yang jelas !

<facility-keybca>tidak menemukan informasi yang menyatakan bahwa keybca akan tidak sinkron jika tidak digunakan selama lebih dari 3 bulan . coba dong yang jelas !</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

internet banking bca enggak sepraktis mandiri online ya

<facility-klikbca>internet banking enggak sepraktis online</facility-klikbca> <facility-aplikasi>enggak sepraktis online</facility-aplikasi>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

mau gue buang keybca gue terserah gue siapa suruh terblokir

<facility-keybca>keybca terblokir</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

bca perlu membenarkan sistem terutama cs enggak jelas ini !

<service-haloBCA>cs enggak jelas</service-haloBCA>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

awal nya keybca nonaktif seperti di gambar .Lalu beberapa saat kemudian bisa normal .eh tahu nya pas dicoba transaksi malah gagal

<facility-keybca>keybca nonaktif transaksi gagal</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Lah percuma kemarin saya daftar i - banking tetapi belum punya keybca , jadi enggak bisa transfer lain kali yang jelas dong cs - nya

<facility-klikbca>i - banking enggak bisa transfer</facility-klikbca> <facility-keybca>belum punya keybca</facility-keybca> <service-cs>yang jelas dong cs</service-cs>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Sudahlah gue hapus saja itu komplain .Solusi nya ribet dikit bayar pakai keybca .Padahal ku suka sekali layanan KlikPay .

<facility-keybca>ribet dikit bayar keybca</facility-keybca> <facility-klikpay>suka sekali KlikPay</facility-klikpay>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

KeyBCA sekitar 3 bulan tidak digunakan , KlikBCA sekarang belum terblokir , tetapi sudah 2x gagal nih

<facility-klikbca>KlikBCA sudah 2x gagal</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Ya Allah sekarang ganti keybca bayar nya 50 ribu mahal banget

<facility-keybca>ganti keybca mahal banget</facility-keybca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Aku mau aktifkan klikbca lama-lama ini mah ;-; klikbca lebih mantap lagi karena bisa dibuka lewat laptop .Jadi bisa salin tempel doang ;-;

<facility-klikbca>klikbca lebih mantap lagi karena bisa dibuka lewat laptop</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Widih klikbca sekarang sudah mantap bisa transfer antarbank , enggak perlu ribet lagi

<facility-klikbca>klikbca sudah mantap transfer antarbank enggak perlu ribet lagi</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Hm Lagi mau dekat-dekat waktu pemisahan catatan transaksi , klikbca mengadat .Mantap banget ini bikin keringatan .

<facility-klikbca>klikbca mengadat</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

klikpay ini ribet , sebal , sebal , sebal !

<facility-klikpay>klikpay ribet , sebal , sebal , sebal</facility-klikpay>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Kalau kayak begini sinyal telepon genggam pengin ke warnet deh , pengin buka klikBCA terus beli pulsa internet .Sebal !

<facility-klikbca>supersebal klikbca</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

klikbca lagi eror enggak sih ?bisa masuk tetapi enggak bisa dipakai transaksi .sebal .

<facility-klikbca>klikbca eror bisa masuk sebal</facility-klikbca> <product-kartu kredit>enggak bisa dipakai transaksi</product-kartu kredit>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

sebal adalah ketika mau cek transaksi klikbca eror .merusak suasana hati yang lagi semangat mau mendata : |

<facility-klikbca>sebal cek transaksi klikbca eror merusak suasana hati</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

pagi-pagi buka klikbca bukan nya senang malah sebal , cih

<facility-klikbca>buka klikbca sebal</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Mandiri e - banking enggak semudah klikbca !Percuma dong !Sebal deh masa gagal melulu .

<facility-aplikasi>e - banking enggak semudah klikbca Percuma dong ! Sebal deh masa gagal melulu</facility-aplikasi> <facility-klikbca>e - banking enggak semudah klikbca</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

semua , ada yang mengalami problem di KlikBCA enggak ya ?Sejak semalam enggak bisa transaksi I - banking nih .Sebal banget kalau pas lagi butuh .

<facility-klikbca>KlikBCA enggak bisa transaksi Sebal banget</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Klik BCA terkunci sebal bangetlah !harus ke BCA lagi .berengsek banget hari ini .

<facility-klikbca>Klik BCA terkunci sebal bangetlah berengsek banget hari ini</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Ini kenapa ya , KlikBCA kagak bisa diakses *sebal*

<facility-klikbca>KlikBCA kagak bisa diakses * sebal</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

paling sebal kalau malam-malam begini baik klikbca maupun e - banking mandiri pada mati semua .kenapa mesti berbarengan sih ?!butuh tahu gue !

<facility-aplikasi>paling sebal e - banking mati semua</facility-aplikasi> <facility-klikbca>paling sebal klikbca mati semua</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Sebal banget sama klikbca yang sudah eror seharian ini .

<facility-klikbca>Sebal banget klikbca eror seharian</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Ini klikBCA kenapa sih enggak benar-benar .sebal

<facility-klikbca>klikBCA enggak benar-benar . sebal</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Klikbca lagi susah banget diakses , sebal .apa ada hubungan nya dengan berita semua kartu bca bakal diblok

<facility-klikbca>Klikbca susah banget diakses sebal</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Kayak nya @IndosatCare parah banget , sinyal kata nya 4G plus tetapi buka web kompas , merdeka , sama klikbca saja enggak bisa !

<facility-m-bca>M - banking eror kan parah</facility-m-bca> <facility-klikbca>klikbca eror kan parah</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@kIikbca 2 hari ini susah akses klikbca bisnis .lambat dan tiba-tiba dibilang diblokir .parah

<facility-klikbca>susah akses klikbca bisnis lambat dan tiba-tiba dibilang diblokir . parah</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Gusti klikBCA transfer gagal melulu .Parah banget ganggu kerja saja ck

<facility-klikbca>klikBCA transfer gagal melulu Parah banget ganggu kerja saja ck</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

Cuma buka klikbca doang saja sampai sejam , itu pun cuma bisa dipakai cek saldo , mau transfer tetap enggak bisa .@myXLCare buruk parah !

<facility-klikbca>buka klikbca sampai sejam bisa cek saldo transfer enggak bisa</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@bliblidotcom @BlibliCare tadi dah dapat potongan nya , eh sampai Web BCA klikpay , eror .Parah

<facility-klikpay>klikpay eror . Parah</facility-klikpay>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA BCA kian hari kian parah .Belanja di tokopedia via klikbca , status nya transaksi GAGAL tetapi saldo dipotong / didebet , dikomplain kata nya proses 1 minggu

<service-general>kian hari kian parah</service-general> <facility-klikbca>Belanja di tokopedia klikbca transaksi GAGAL tetapi saldo dipotong / didebet</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA admin bagaimana sampai sekarang klikBCA saya masih terblokir , padahal yang salah BCA - ny , parah !

<facility-klikbca>klikBCA masih terblokir parah</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA wah parah awal pekan lagi sibuk-sibuk nya transaksi , klikbca malah eror .

<facility-klikbca>transaksi klikbca eror</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@TelkomCare baru tanggal 11 saya kemarin enggak bisa bayar karena eror klikbca sekarang telepon mati semua , parah banget telat bayar tanpa konfirmasi dimatikan

<facility-klikbca>enggak bisa bayar karena eror klikbca</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

parah internet bangking #bri #ibangking sial kalah sama klikbca #bca belum apa-apa sudah terblokir , padahal konektivitas internet mulus

<facility-aplikasi>parah internet bangking kalah sama klikbca belum apa-apa sudah terblokir , padahal konektivitas internet mulus</facility-aplikasi> <facility-klikbca>internet bangking # # ibangking sial kalah sama klikbca</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@pln_123 kok enggak bisa beli pulsa listrik via apa pun sih ini ?Atm bca bni enggak bisa .Klikbca juga enggak bisa .Parah !

<facility-atm>beli pulsa listrik Atm enggak bisa</facility-atm> <facility-klikbca>Klikbca enggak bisa</facility-klikbca> <general>Parah</general>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

@HaloBCA klikbca anda bermasalah .parah !

<facility-klikbca>klikbca bermasalah . parah</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

KlikBCA oh KlikBCA , eror mu kok parah .:( (

<facility-klikbca>KlikBCA eror mu kok parah</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

klikbca.com parah gila

<facility-klikbca>klikbca.com parah gila</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

sampai klikbca sama kpk situs nya gangguan !tahu mengapa - _ - " !

<facility-klikbca>klikbca situs gangguan</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

BCA Klikpay enggak bisa masuk .parah .enggak ada yang benar .

<facility-klikpay>Klikpay masuk</facility-klikpay> <facility-klikbca>enggak bisa parah . enggak ada yang benar</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output:

klikBCA eror .saldo nya sebegitu terus dari kemarin .

<facility-klikbca>klikBCA eror</facility-klikbca>

Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text. Input format: A sentence or short paragraph in Indonesian. Output format: XML-style tags containing the aspect and corresponding text. Aspect list: facility-BCA Mobile facility-EDC facility-NFC facility-aplikasi facility-atm facility-deposit box facility-e-channel facility-general facility-kantor facility-keybca facility-klikbca facility-klikpay facility-m-bca facility-mesin cs digital facility-payroll facility-phone banking general general-iklan general-promo product-KKB product-KMK product-KPR product-KUR product-asuransi product-deposito product-e-money product-flazz product-general product-giro product-kartu debit product-kartu kredit product-kartu-kredit product-pinjaman product-sakuku product-simpanan service-cs service-customer center service-general service-haloBCA service-kantor cabang service-karyawan service-prioritas service-satpam service-telemarketing service-teller service-tukang parkir Rules for extraction: 1. Identify the most relevant aspect(s) from the list for the given input. 2. Extract the minimal span of text that accurately represents the aspect. 3. If multiple aspects are present, extract each one separately. 4. If no relevant aspect is found, output "NONE" Examples: Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah! Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general> Input: Teller Mandiri yang baru ini ribet sekali. Output: <service-teller>Teller ribet sekali</service-teller> Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit> Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari. Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile> Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna. Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general> Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet . Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca> Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA . Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile> Input: Cuaca hari ini cerah sekali. Output: NONE Handling ambiguity: - If a sentence could belong to multiple aspects, write all of them Now, given the input text below, extract the relevant aspects and text: Input: [text] Output: