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absa_bca_v2

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AC di ATM Mandiri Depok tidak berfungsi

<facility-atm>AC ATM tidak berfungsi</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:

ATM BNI paling bagus fasilitasnya

<facility-atm>ATM paling bagus</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:

Transfer lewat ATM BCA sering banget ditolak

<facility-atm>Transfer ATM sering banget ditolak</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:

Bayar BPJS lewat ATM Mandiri sekarang sudah bisa

<facility-atm>Bayar BPJS ATM sudah bisa</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:

tampilan mesin ATM BCA jelek banget

<facility-atm>tampilan mesin ATM jelek banget</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:

Cek saldo di ATM Permata tidak pernah bisa

<facility-atm>Cek saldo ATM tidak pernah bisa</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:

Gila, ATM Permata susah banget dicarinya

<facility-atm>ATM susah banget dicarinya</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:

ATM BCA sering macet

<facility-atm>ATM sering macet</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:

BCA Mobile paling sering gagal kalau mau transfer

<facility-BCA Mobile>BCA Mobile sering gagal transfer</facility-BCA Mobile>

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 gangguan terus mau mobile banking mau klikbca sama aja, bca jadi jelek gini

<facility-klikbca>parah gangguan terus klikbca</facility-klikbca> <facility-BCA Mobile>parah gangguan terus mobile banking</facility-BCA Mobile> <general>jelek</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:

Susahnya akses BCA Mobile lewat HP

<facility-BCA Mobile>Susahnya akses BCA Mobile</facility-BCA Mobile>

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 tampilannya jelek banget deh

<facility-BCA Mobile>BCA mobile tampilannya jelek banget</facility-BCA Mobile>

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:

Eror melulu setiap kali mau cek saldo pakai BCA mobile

<facility-BCA Mobile>Eror melulu cek saldo BCA mobile</facility-BCA Mobile>

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 banget pakai BCA mobile kalau mau transaksi

<facility-BCA Mobile>Enak banget BCA mobile transaksi</facility-BCA Mobile>

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:

Simpel dan mudah BCA Mobile itu @BCA

<facility-BCA Mobile>Simpel dan mudah BCA Mobile</facility-BCA Mobile>

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 saya tidak bisa dipakai buat melihat mutasi rekening

<facility-BCA Mobile>BCA Mobile tidak bisa dipakai mutasi rekening</facility-BCA Mobile>

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:

Tampilan baru BCA Mobile tetap jelek

<facility-BCA Mobile>Tampilan baru BCA Mobile jelek</facility-BCA Mobile>

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 beli bulsa lewat BCA Mobile tetapi tidak masuk dari kemarin

<facility-BCA Mobile>beli bulsa BCA Mobile tidak masuk</facility-BCA Mobile>

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 STK, mau ATM, atau pun mobile bankingnya, BCA tidak mengecewakan nasabahnya

<facility-atm>ATM tidak mengecewakan</facility-atm> <facility-m-bca>mobile bankingnya tidak mengecewakan</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:

Bagus nih e-channel BCA

<facility-e-channel>Bagus e-channel</facility-e-channel>

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

Enggak bagus ah e-channel BCA

<facility-e-channel>Enggak bagus e-channel</facility-e-channel>

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

Banyak sekali fasilitas yang diberikan oleh e-channel BCA

<facility-e-channel>Banyak sekali fasilitas yang diberikan e-channel</facility-e-channel>

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

Fungsi mobile banking atau internet banking BCA memang memudahkan penggunanya

<facility-m-bca>mobile banking memudahkan penggunanya</facility-m-bca> <facility-klikbca>internet banking memudahkan penggunanya</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 ada tandingannya e-channel BCA

<facility-e-channel>Enggak ada tandingannya e-channel</facility-e-channel>

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

Semua tampilan e-channel BCA biasa saja

<facility-e-channel>tampilan e-channel biasa saja</facility-e-channel>

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

Tampilan internet banking dan mobile banking BCA kurang kekinian

<facility-m-bca>Tampilan mobile banking kurang kekinian</facility-m-bca> <facility-klikbca>Tampilan internet banking kurang kekinian</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:

Mantap betul e-channel BCA

<facility-e-channel>Mantap betul e-channel</facility-e-channel>

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

BCA Mobile dan KlikBCA memang nomor satu untuk segala fasilitasnya

<facility-BCA Mobile>BCA Mobile nomor satu fasilitasnya</facility-BCA Mobile> <facility-klikbca>KlikBCA nomor satu fasilitasnya</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:

E-channel BCA dilengkapi dengan fitur-fitur transakasi perbankan yang memudahkan nasabahnya

<facility-e-channel>E-channel fitur-fitur transakasi memudahkan</facility-e-channel>

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

BCA e-channel enggak berguna

<facility-e-channel>e-channel enggak berguna</facility-e-channel>

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

Nirguna banget e-channel-nya BCA

<facility-e-channel>Nirguna banget e-channel-nya</facility-e-channel>

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

Sampah asli e-channel BCA

<facility-e-channel>Sampah asli e-channel</facility-e-channel>

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

Enggak kecewa selama ini pakai mobile dan internet banking dari BCA

<facility-m-bca>Enggak kecewa mobile</facility-m-bca> <facility-klikbca>Enggak kecewa internet banking</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:

Transaksi pembayaran toko jadi mudah pakai EDC BCA

<facility-EDC>Transaksi pembayaran toko mudah EDC</facility-EDC>

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 tidak perlu repot lagi bayar cicilan karena sudah bisa di EDC BCA

<facility-EDC>tidak perlu repot bayar cicilan EDC</facility-EDC>

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:

gesek tunai sudah mudah dengan layanan EDC BCA

<facility-EDC>gesek tunai mudah EDC</facility-EDC>

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 Hidup ini jadi mudah karena EDC bisa tarik tunai

<facility-EDC>Hidup ini jadi mudah EDC bisa tarik tunai</facility-EDC>

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 Mesin EDC gangguan terus sudah 3 hari ini

<facility-EDC>Mesin EDC gangguan terus</facility-EDC>

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 sekali mau bayar tol pakai mesin EDC @BCA

<facility-EDC>susah sekali bayar tol mesin EDC</facility-EDC>

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:

Mesin EDC BCA eror terus jadi sulit melakukan transaksi

<facility-EDC>Mesin EDC eror sulit transaksi</facility-EDC>

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 EDC anda mati dan tidak bisa disetel ulang. Pembayaran jadi susah ini

<facility-EDC>EDC mati dan tidak bisa disetel ulang Pembayaran susah</facility-EDC>

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:

transaksi saya sudah gagal dua kali di EDC @BCA. Semoga tidak ikut terdebit

<facility-EDC>transaksi gagal dua kali EDC</facility-EDC>

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:

tombol enter EDC BCA keras dan sulit ditekan

<facility-EDC>tombol enter EDC keras dan sulit ditekan</facility-EDC>

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 internet banking KlikBCA sering kali keluar dengan sendirinya sehingga sangat mengganggu kenyamanan ketika bertransaksi.

<facility-klikbca>KlikBCA sering kali keluar dengan sendirinya</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 BCA, koneksi internet saya stabil, tetapi sulit sekali masuk ke klikBCA

<facility-klikbca>sulit sekali masuk 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:

@BCA klikBCA malah mati saat cek mutasi rekening

<facility-klikbca>klikBCA mati cek 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:

BCA kalau mau perbaikan situs klikBCA jangan di jam kerja, bikin susah untuk transaksi

<facility-klikbca>perbaikan situs klikBCA di jam kerja , bikin susah untuk 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:

klikBCA saya tidak bisa dipakai untuk cek informasi saldo. Mohon perbaikannya pihak BCA

<facility-klikbca>klikBCA tidak bisa dipakai cek informasi saldo</facility-klikbca>

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

@BCA bisa masuk ke klikbca, tetapi kalau mau transaksi gagal terus

<facility-klikbca>bisa masuk klikbca transaksi gagal terus</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:

salut sama internet banking BCA, perbaikan sistemnya cepat banget

<facility-klikbca>salut internet banking perbaikan sistemnya cepat 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:

@BCA tampilan klikbca di peramban firefox tidak sempurna, payah

<facility-klikbca>tampilan klikbca tidak sempurna , payah</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 kesulitan cek saldo karena internet banking bca tidak bisa diakses

<facility-klikbca>kesulitan cek saldo internet banking tidak 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:

klikbca sering kaluar sendiri beberapa saat setelah masuk

<facility-klikbca>klikbca sering kaluar sendiri</facility-klikbca>

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

BCA KlikPay membuat bayar belanja daring jadi praktis dan terpercaya

<facility-klikpay>KlikPay bayar belanja daring praktis dan terpercaya</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:

terima kasih BCA. sekarang jadi mudah sekali transaksi klikpay lewat hp

<facility-klikpay>mudah sekali transaksi 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:

transaksi daring sudah tidak ribet berkat klikpay bca

<facility-klikpay>transaksi daring tidak ribet 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:

bayar domain/hosting makin mudah dengan fitur bca klikpay

<facility-klikpay>bayar domain / hosting makin mudah 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:

@BCA klikpay kurang responisf tampilannya. jadi sulit bisa dibuka di ukuran layar tertentu

<facility-klikpay>klikpay kurang responisf tampilannya sulit bisa dibuka di ukuran layar tertentu</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:

pendaftaran klikpay bca mudah, cepat, dan grattis. Segera daftar klikpay BCA

<facility-klikpay>pendaftaran klikpay mudah , cepat , dan grattis</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:

bayar AXA Indonesia kini makin mudah, bisa lewat bca klikpay

<facility-klikpay>bayar AXA Indonesia makin mudah 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:

saya baru bikin bca klikpay, urusan keuangan saya langsung jadi mudah

<facility-klikpay>klikpay urusan keuangan saya langsung jadi mudah</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:

BCA KlikPay itu metode pembayaran untuk berbelanja online yang praktis dan mudah.

<facility-klikpay>KlikPay metode pembayaran untuk berbelanja online yang praktis dan mudah</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:

Kini semakin mudah bertransaksi di Pointer menggunakan KlikPay BCA

<facility-klikpay>semakin mudah bertransaksi di Pointer 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:

biaya transaksi m-bca mahal sekali @BCA

<facility-m-bca>biaya transaksi m-bca mahal sekali</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:

payah bannget m-bca tidak bisa diakses pakai jaringan cdma

<facility-m-bca>payah bannget m-bca tidak bisa diakses pakai jaringan cdma</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:

Gue cenderung masih konvensional karena masih nyaman dengan m-BCA @BCA

<facility-m-bca>nyaman m-BCA</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 kok susah sekali mau tambah nomor rekening di m-bca

<facility-m-bca>susah sekali tambah nomor rekening m-bca</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 M-bca payah banget, masih tidak bisa cek saldo flazz

<facility-m-bca>M-bca payah banget tidak bisa cek saldo flazz</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 dengan M-bca-nya sangat baik, memberikan kemudahan bertransaksi.

<facility-m-bca>M-bca-nya sangat baik , memberikan kemudahan bertransaksi</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:

M-bca jelek nih, belum ada notifikasi saldo masuk @BCA

<facility-m-bca>M-bca jelek belum ada notifikasi saldo masuk</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:

Aplikasi m-bca ini sangat membantu, terlebih lagi dengan semua kemudahan yg disuguhkan

<facility-m-bca>m-bca sangat membantu</facility-m-bca>

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

kalau malam hari mau cek saldo m-bca selalu gagal ya @BCA

<facility-m-bca>cek saldo m-bca selalu gagal</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 setiap saya mau mendaftarkan nomor rekening untuk transfer antar rekening selalu enggak bisa. Jelek banget m-bca

<facility-m-bca>mendaftarkan nomor rekening selalu enggak bisa Jelek banget m-bca</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:

sudah 5 tahun jadi nasabah BCA dan sangat memuaskan

<general>sangat memuaskan</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:

Payah banget BCA, suka pilih kasih sama nasabanya sendiri

<general>Payah banget suka pilih kasih sama nasabanya sendiri</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:

mau urus apa-apa di BCA selalu dipersulit cuma karena saya nasabah biasa

<service-general>selalu dipersulit</service-general>

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

bank yang bagus dan keren ya BCA, ada di mana-mana

<general>bank yang bagus dan keren</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:

bawa BCA ke luar negeri sudah pasti paling enak

<general>paling enak</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:

semua bank kalah sama bca kinerjanya. mantap BCA

<general>semua bank kalah sama bca kinerjanya . mantap</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:

BCA menurut gue bank paling bagus dari banyak segi

<general>bagus</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:

BCA sudah terkenal bagusnya di kawasan Asean

<general>sudah terkenal bagusnya di kawasan Asean</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:

Sekeluarga jadi nasabah BCA, BCA tidak pernah mengecewakan

<general>tidak pernah mengecewakan</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:

Iklan bank bca bikin kaget. keren konsepnya

<general-iklan>Iklan bikin kaget keren konsepnya</general-iklan>

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, telah menayangkan iklan yang tidak sehat, parah

<general-iklan>iklan tidak sehat , parah</general-iklan>

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:

iklan layanan perbankan yang bagus ini punya @bca

<general-iklan>iklan bagus</general-iklan>

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:

video di iklan bca terbaru bagus banget penggarapannya

<general-iklan>video iklan bagus banget penggarapannya</general-iklan>

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 iklan di portal berita jadi ganggu orang baca saja

<general-iklan>iklan ganggu</general-iklan>

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:

iklan BCA menipu, kenyataannya tidak sesuai sama yang diiklankan

<general-iklan>iklan menipu</general-iklan>

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 iklan BCA, benar-benar membuat saya ingin jadi nasabahnya

<general-iklan>iklan benar-benar membuat saya ingin jadi nasabahnya</general-iklan>

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:

Iklan BCA ini bangkai deh, diulang-ulang melulu

<general-iklan>Iklan bangkai deh , diulang-ulang melulu</general-iklan>

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 pasang iklan gede tutup lampu merah, bikin rusuh saja

<general-iklan>iklan bikin rusuh</general-iklan>

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:

iklan bca saja bikin gue ketawa, payah banget konsepnya

<general-iklan>iklan payah banget konsepnya</general-iklan>

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 bunganya terlalu kecil

<general>terlalu kecil</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:

Bunga BCA selalu menarik hati nasabah

<general>menarik hati nasabah</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:

Biaya pemakaian semua produk BCA termasuk mahal

<product-general>Biaya produk mahal</product-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:

Dibandingkan dengan BRI atau BNI, bank BCA terkenal memiliki produk yang lebih inovatif

<product-general>produk lebih inovatif</product-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:

Bunga bank BCA tidak pernah mengecewakan nasabah

<general>tidak pernah mengecewakan nasabah</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:

BCA memang menawarkan simpanan dan kredit paling menarik

<product-simpanan>simpanan paling menarik</product-simpanan> <product-kartu kredit>kredit paling menarik</product-kartu kredit>

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

Mulai dari kartu kredit, kredit tanpa agunan, simpanan, sampai kredit pemilikan rumah BCA memang dikenal paling menjanjikan

<product-general>kartu kredit , kredit tanpa agunan , simpanan , sampai kredit pemilikan rumah paling menjanjikan</product-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:

Tidak salah gue memilih produk-produk BCA untuk keseharian gue.

<product-general>Tidak salah gue memilih produk-produk</product-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: