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absa_bca_v2

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Klikbca eror ya .Parah ah

<facility-klikbca>Klikbca eror ya . 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:

parah banget !Buka klikbca , go mobile CIMB gagal melulu , pret benar

<facility-aplikasi>parah banget Buka go mobile gagal melulu , pret benar</facility-aplikasi> <facility-klikbca>parah banget Buka klikbca gagal melulu , pret 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:

Parah ni klikbca bisa transaksi nya cuma jam kerja doang x_x huyuh

<facility-klikbca>Parah klikbca transaksi cuma jam kerja doang</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 makin parah .bagaimana sih ?

<facility-klikbca>klikbca makin 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:

Mau masuk ke klikBCA di web kok lambat banget ya ?Penuh ?

<facility-klikbca>masuk klikBCA lambat 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:

Wah parah nih #klikbca gangguan gagal transaksi .Rekening Sampai terblokir aduh .

<facility-klikbca>parah klikbca gangguan gagal transaksi . Rekening Sampai terblokir aduh</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 terblokir melulu , sistem i - banking - nya parah benar .

<facility-klikbca>klikbca terblokir melulu sistem i - banking - nya parah 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:

semua kencang memuat nya klikBca saja yang parah sudah 3x gue kayak begini transaksi

<facility-klikbca>klikBca parah transaksi</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 seluler @klik_bca kok " internal server error " melulu di tengah-tengah lagi transfer .Parah nih

<facility-klikbca>klik_bca transfer 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 gangguan , pin pada terblokir semua !Bagus !Registrasi ulang !Buang-buang waktu saja !Bisa - bisan nya BCA eror kayak begini !Parah !

<facility-klikbca>KlikBCA gangguan pin terblokir semua Registrasi ulang Buang-buang waktu saja eror kayak begini ! 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:

sistem pembayaran klikBCA eror .Parahlah !

<facility-klikbca>sistem pembayaran 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:

server klikbca lambat parah .

<facility-klikbca>server klikbca lambat 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:

server klikbca lambat sekali parah , gembel #bca

<facility-klikbca>server klikbca lambat sekali parah , gembel</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 parah kok enggak bisa terkoneksi .Ha

<facility-klikbca>Klikbca parah kok enggak bisa terkoneksi</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:

Rusak nya e - banking klikbca sudah tergolong parah , sangat sering dan lama .

<facility-klikbca>Rusak nya e - banking klikbca sudah tergolong parah , sangat sering dan lama</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 , KlikBCA - nya macet

<facility-klikbca>parah KlikBCA macet</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 masuk ke klikbca kok susah ya

<facility-klikbca>masuk klikbca susah</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 tahi nih kalau transfer beda bank susah banget

<facility-klikbca>klikbca tahi transfer beda bank susah 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:

bank BUMN besar sekelas @mandiricare lambat banget untuk buka aplikasi daring !klikBCA cuma butuh 2 detik untuk akses .

<facility-aplikasi>lambat banget buka aplikasi daring</facility-aplikasi> <facility-klikbca>aplikasi daring klikBCA cuma butuh 2 detik untuk akses</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 klikBCA lagi gangguan Dari kemarin coba buka susah banget .

<facility-klikbca>klikBCA lagi gangguan buka susah 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:

Saya buka klikbca via telepon genggam kok susah ya , padahal internet nya lancar @HaloBCA

<facility-klikbca>buka klikbca susah</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:

Tolong diperbaiki dong klikbca - nya .Saya jadi susah melakukan pembayaran .

<facility-klikbca>klikbca susah pembayaran</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 mau masuk klikbca susah benar ya @HaloBCA

<facility-klikbca>masuk klikbca susah 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:

aku pernah , kadang berhasil 1x24 jam kadang balik lagi saldo nya ke rekening kita agak susah memang kalau dari klikbca :( ((

<facility-klikbca>agak susah 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:

Susah banget ini 1500888 ditelepon hari ini .Dan kenapa klikbca enggak bisa diakses sih

<service-haloBCA>Susah banget ini 1500888 ditelepon</service-haloBCA> <facility-klikbca>klikbca enggak bisa diakses</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 klikbca susah mengakses mutasi rekening .

<facility-klikbca>klikbca susah mengakses mutasi rekening</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:

Susah benar akses klikbca dari Australia , sudah pakai 2 penyedia jasa yang beda tetap lelet dan akhirnya gagal .Dibenarkan dong , @HaloBCA @BankBCA .

<facility-klikbca>Susah benar akses 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:

@HaloBCA masuk ke klikbca susah banget .Pin harus numerik .Padahal yang dimasukkan ya angka semua .

<facility-klikbca>masuk klikbca susah 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:

Mau buka klikbca mau transfer bayar kas saja susah banget deh lama saya enggak bayar kas .

<facility-klikbca>klikbca transfer bayar kas susah 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:

Yang susah buka e - banking klikbca di google chrome

<facility-klikbca>susah buka 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 beda bank ini susah banget masuk nya .Karena nama orang dan nomor ditik manual .enggak muncul otomatis .

<facility-klikbca>KlikBCA beda bank susah banget masuk 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:

Susah amat deh mau aktifkan klikpay bca .

<facility-klikpay>Susah amat aktifkan 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:

ini klikbca kenapa sih susah banget dibuka , padahal situs lain lancar jaya ~ : v

<facility-klikbca>klikbca susah banget dibuka</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:

Mau tranfer pakai klikbca ke beberapa rekening susah banget , suruh masuk ulang 10 menit lagi terus :( @ebanking_bca

<facility-klikbca>tranfer klikbca susah 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:

Ini Klikbca kok buat masuk susah betul .

<facility-klikbca>Klikbca masuk susah betul</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:

kenapa ini klikbca susah benar diakses

<facility-klikbca>klikbca susah benar diakses</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:

sekarang tambah susah ya transaksi klikbca transfer ke bank lain .huft .@HaloBCA

<facility-klikbca>tambah susah klikbca transfer ke bank lain</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:

Lah klikbca susah banget masuk nya > <

<facility-klikbca>klikbca susah banget masuk</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:

enggak jelas banget promo klikpay bca sama blibli ,

<facility-klikpay>enggak jelas banget promo 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:

Klikbca individual susah amat dibuka di telepon genggam ya argh

<facility-klikbca>Klikbca individual susah amat dibuka</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 klikbca kenapa susah banget sih masuk nya , harus berkali-kali menunggu 10 menit :/

<facility-klikbca>klikbca susah banget masuk</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:

daring klikbca mulai susah lagi .Padahal masih pagi lo .

<facility-klikbca>klikbca mulai susah 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:

benaran deh buka klikbca lagi susah benar ; ( marah padahal mau bayar daring .@KartuKreditBCA

<facility-klikbca>buka klikbca susah 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 susah banget dibuka , lagi perlu kak

<facility-klikbca>klikbca susah banget dibuka</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:

mau buka klikbca saja susah benar dari tadi eh .

<facility-klikbca>buka klikbca susah 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 kenapa susah amat dibuka dari telepon genggam

<facility-klikbca>Klikbca susah amat dibuka dari telepon genggam</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 susah amat dibuka nya

<facility-klikbca>klikbca susah amat dibuka</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:

Sekali buka laptop langsung dibikin mumet sama klikbca yang bikin ribet enggak tahu lagi butuh banget pakai acara susah masuk !

<facility-klikbca>dibikin mumet klikbca bikin ribet susah masuk</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 susah banget deh .

<facility-klikbca>klikbca susah 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:

@HaloBCA klikbca susah banget diakses , pemuat halaman enggak mau , tetapi ke website lain lancar aman saja dan cepat terbuka nya .

<facility-klikbca>klikbca susah banget diakses</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:

Dari pagi saya coba buka klikbca susah banget kalau pun masuk , pas mau transaksi nya susah :(

<facility-klikbca>buka klikbca susah banget transaksi susah</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:

Susah benar hendak berurusan dengan membawa KlikBCA ini .: s

<facility-klikbca>Susah benar 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:

Akhir bulan klikbca susah dibuka coy .

<facility-klikbca>klikbca susah dibuka</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:

tiap mau bayar lewat klikbca buat bayar @tiket susah amat ya .kata nya transaksi gagal .padahal berhasil kok :( ((

<facility-klikbca>klikbca bayar susah amat kata nya transaksi gagal . padahal berhasil kok</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:

Buka klikbca susah benar dari tadi

<facility-klikbca>Buka klikbca susah 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:

Mampus klikbca susah diakses .Ini terseret isi nya mungkin .: |

<facility-klikbca>Mampus klikbca susah diakses</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 klikbca susah diakses di telepon genggam - _ -

<facility-klikbca>klikbca susah diakses di telepon genggam</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:

susah nya kalau mau transfer ke bank lain di klikbca - ___ -

<facility-klikbca>susah transfer ke bank lain 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:

Pakai KlikBCA semua jadi gampang , enggak perlu repot lagi mengantre di atm. Hidup sudah susah , jangan dibikin tambah susah !

<facility-klikbca>KlikBCA semua jadi gampang</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:

Sekarang susah amat mau transfer ke rekening lain lewat klikbca .berasa balik ke zaman purba mesti ke atm

<facility-klikbca>susah amat transfer ke rekening lain 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:

ini klikbca kenapa susah banget sih masuk nya

<facility-klikbca>klikbca susah banget masuk</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:

Dibikin repot transfer ke bank lain di KlikBCA mungkin trik agar uang nasabah cuma memutar-mutar di dalam saja .susah untuk keluar .

<facility-klikbca>Dibikin repot transfer ke bank lain 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:

Aduh klikbca , mau transfer saja susah banget sih .sampai harus daftar dahulu ke HaloBCA .Malas banget - _ -

<facility-klikbca>klikbca transfer susah 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:

@HaloBCA bca klikpay susah registrasi , alias setelah daftar enggak bisa konfirmasi ( enggak dapat sms nya ) , daftar via klikbca .

<facility-klikpay>klikpay susah registrasi enggak bisa konfirmasi</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:

klikbca sedang bermasalah sore ini .Mau transfer saja susah amat .Mau telepon HaloBCA , paling disuruh cek virus+format .Lah ini lo dari Linux

<facility-klikbca>klikbca bermasalah transfer susah amat</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:

Akses klikbca itu bikin emosi jiwa deh , susah banget bisa mulus masuk , yang ada selalu eror .Dan harus ulang 10 menit

<facility-klikbca>Akses klikbca bikin emosi jiwa deh , susah banget bisa mulus masuk , yang ada selalu 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:

Klikbca jelek amat 2 hari ini , susah banget mau cek mutasi doang

<facility-klikbca>Klikbca jelek amat susah banget cek mutasi</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 gangguan bikin susah orang

<facility-klikbca>Klikbca gangguan bikin susah orang</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 susah banget diajak kerja hari ini : |

<facility-klikbca>klik bca susah banget diajak kerja 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:

Dari tadi sore mau bayar CC atm - nya enggak bisa , sekarang lewat klikbca juga enggak bisa , mau bayar kok malah susah ya .

<facility-atm>bayar CC atm enggak bisa</facility-atm> <facility-klikbca>bayar CC klikbca 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:

Dari kemarin susah banget mau isi pulsa mentari via klikbca .Sampai masa aktif nya habis .Hiks .

<facility-klikbca>susah banget isi pulsa 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:

Ah sial lah klikbca ini , mau transfer saja susah benar !

<facility-klikbca>sial klikbca transfer susah 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:

daftar internet banking klikbca kayak babi susah sekali agh .

<facility-klikbca>daftar klikbca kayak babi susah sekali</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:

Susah amat koneksi klikbca sekarang .sudah 2 hari berturut-turut begitu .Huh !

<facility-klikbca>Susah amat koneksi 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:

mentang-mentang gajian klikbca susah banget diakses nya eror melulu .aduh

<facility-klikbca>klikbca susah banget diakses eror melulu</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:

M - Banking nya BCA ribet sih menurut saya .Lebih mudah dan lebih cepat Mandiri Mobile .

<facility-m-bca>M - Banking ribet</facility-m-bca> <facility-aplikasi>Lebih mudah dan lebih cepat 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:

@HaloBCA transaksi pakai BCA mobile android cepat banget lancar jaya terima kasih .: * kecup

<facility-m-bca>transaksi BCA mobile cepat banget lancar jaya</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:

Enak nya bca akses internet nya dan mobile banking nya cepat dan gampang ,

<facility-klikbca>akses internet cepat dan gampang</facility-klikbca> <facility-m-bca>mobile banking cepat dan gampang</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:

dikira @bankmandiri saja yang aplikasi mobile banking nya busuk .Ternyata @bca juga enggak beda .

<facility-aplikasi>mobile banking busuk</facility-aplikasi> <facility-m-bca>mobile banking busuk</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:

@HaloBCA parah gangguan terus mau mobile banking mau klikbca sama saja , bca jadi jelek begini ya heran

<facility-m-bca>parah gangguan terus mobile banking</facility-m-bca> <facility-klikbca>parah gangguan terus klikbca</facility-klikbca> <general>jelek begini</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:

mobile banking BCA ini cuma transaksi tunai tanpa kartu nya saja yang berfaedah .Lainnya jelek .

<facility-m-bca>mobile banking transaksi tunai tanpa kartu berfaedah Lainnya jelek</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:

Belum kelar kendala mobile banking BCA , sekarang menambah kendala ATM .

<facility-m-bca>Belum kelar kendala mobile banking</facility-m-bca> <facility-atm>menambah kendala 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:

Bisa isi flazz dong BCA .E-money saja bisa dari mobile banking sama tokopedia .kalah nih

<product-flazz>isi flazz kalah nih</product-flazz> <product-e-money>isi E-money bisa dari mobile banking sama tokopedia</product-e-money>

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 mobile enggak bisa diakses nih , mau transaksi di rumah jadi ke atm deh ganggu libur saja pft

<facility-m-bca>bca mobile enggak bisa diakses</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:

mobile banking bni saja masih lebih bagus daripada bca

<facility-aplikasi>mobile banking lebih bagus daripada</facility-aplikasi> <facility-m-bca>mobile banking saja masih lebih bagus</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:

Mandiri mobile ini lemot banget ya .gue memakai bca mobile lancar-lancar saja perasaan

<facility-aplikasi>mobile lemot banget</facility-aplikasi> <facility-m-bca>bca mobile lancar-lancar saja</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:

@HaloBCA bca mobile kok sudah sebulan ini enggak bisa memasukkan daftar transfer baru ya , selalu eror dan hanya ikon memutar-mutar saja .benarin dong

<facility-m-bca>bca mobile enggak bisa memasukkan daftar transfer baru selalu eror dan hanya ikon memutar-mutar saja</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:

Kode akses mobile bca bisa terblokir 2x sebulan begini .kacau

<facility-m-bca>Kode akses mobile bca terblokir 2x sebulan begini . kacau</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:

setiap bulan bca mobile gue terblokir - , - bikin penasaran saja !

<facility-m-bca>setiap bulan bca mobile gue terblokir</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 mobile terblokir di kala butuh - ,

<facility-m-bca>Bca mobile terblokir</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:

Justru saya hampir tidak pernah mengalami kendala layanan pembayaran kalau pakai BNI Mobile

<facility-aplikasi>tidak pernah mengalami kendala pembayaran 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:

Akses internet banking BNI mudah, transaksi juga cepat

<facility-aplikasi>internet banking mudah transaksi cepat</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:

mobile banking BNI tidak pernah mengecewakan

<facility-aplikasi>mobile banking tidak pernah mengecewakan</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:

Bayar toko online lewat internet banking Mandiri sering banget terjadi eror

<facility-aplikasi>Bayar toko online internet banking sering banget terjadi eror</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:

bayar cicilan rumah pakai mobile banking permata ternyata sulit

<facility-aplikasi>bayar cicilan rumah mobile banking sulit</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:

baru pertama kali pakai fasilitas internet banking dari Bank Permata, ternyata susah aksesnya

<facility-aplikasi>internet banking susah aksesnya</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:

transfer uang jadi nyaman dengan layanan internet banking Danamon

<facility-aplikasi>transfer nyaman internet banking</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:

BNI mobile banking juara untuk layanan internet banking.

<facility-aplikasi>mobile banking juara</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:

Mudah, cepat, aman, ya pakai internet banking bank BRI

<facility-aplikasi>Mudah , cepat , aman internet banking</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:

BNI Mobile banking repot banget mau akses saja

<facility-aplikasi>Mobile banking repot banget akses</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: