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absa_bca_v2

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Persyaratan KUR di BCA tidak konsisten

<product-KUR>Persyaratan KUR tidak konsisten</product-KUR>

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

Pinjaman tunai di BCA prosesnya mudah dan cepat

<product-pinjaman>Pinjaman tunai prosesnya mudah dan cepat</product-pinjaman>

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

Pagi tadi mengajukan pinjaman modal ke BCA, ternyata cepat

<product-pinjaman>mengajukan pinjaman modal cepat</product-pinjaman>

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

Sulit sekali saya mengajukan pinjaman di BCA

<product-pinjaman>Sulit sekali mengajukan pinjaman</product-pinjaman>

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

Pinjaman lunak dari BCA sekarang mudah

<product-pinjaman>Pinjaman lunak mudah</product-pinjaman>

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

<product-pinjaman>Bunga pinjaman paling tinggi</product-pinjaman>

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

<product-pinjaman>mengajukan pinjaman enak</product-pinjaman>

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

Sulitnya mengajukan pinjaman di BCA. Syaratnya segudang

<product-pinjaman>Sulitnya mengajukan pinjaman Syaratnya segudang</product-pinjaman>

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

Jangan pernah pakai pinjaman BCA. Prosedur pelunasannya ribet banget

<product-pinjaman>pinjaman pelunasannya ribet banget</product-pinjaman>

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

<product-pinjaman>Mantap sekarang bisa mengajukan pinjaman</product-pinjaman>

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

Bolak-balik urus pengajuan pinjaman di BCA ditolak terus

<product-pinjaman>pengajuan pinjaman ditolak terus</product-pinjaman>

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

brizzi sering eror kalau mau dipakai bayar tol

<product-e-money>brizzi sering eror bayar tol</product-e-money>

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

berkali-kali kartu brizzi sulit terbaca di gerbang tol

<product-e-money>brizzi sulit terbaca di gerbang tol</product-e-money>

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

Brizzi kartunya gampang rusak

<product-e-money>Brizzi gampang rusak</product-e-money>

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

Kartu mandiri e-money sulit terbaca di gerbang masuk stasiun

<product-e-money>e-money sulit terbaca di gerbang masuk stasiun</product-e-money>

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

Top up e-money di area malang sulit banget

<product-e-money>Top up e-money sulit banget</product-e-money>

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

sering banget mandiri e-money rusak dan susah terdeteksi

<product-e-money>e-money rusak dan susah terdeteksi</product-e-money>

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

Keluar masuk tol jadi semakin mudah pakai kartu brizzi BRI

<product-e-money>Keluar masuk tol jadi semakin mudah brizzi</product-e-money>

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

Beli bensin di SPBU sudah bisa pakai kartu e-money

<product-e-money>Beli bensin di SPBU sudah bisa e-money</product-e-money>

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

cek saldo e-money sudah bisa lewat hp

<product-e-money>cek saldo e-money sudah bisa lewat hp</product-e-money>

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

jelek banget desain kartu brizzi bri yang baru

<product-e-money>jelek banget desain brizzi</product-e-money>

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

top up flazz gagal terus dari kemarin

<product-flazz>top up flazz gagal terus</product-flazz>

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

<general>payah</general> <product-flazz>isi flazz gagal terus</product-flazz>

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

Pakai flazz memang paling simpel

<product-flazz>flazz paling simpel</product-flazz>

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

belanja sekarang jadi semakin mudah berkat flazz bca

<product-flazz>belanja semakin mudah</product-flazz>

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

Ribet banget mau top up flazz BCA

<product-flazz>Ribet banget top up flazz</product-flazz>

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

<product-flazz>tap masuk stasiun susah benar flazz</product-flazz>

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

flazz BCA sering tidak terbaca kalau naik transjakarta

<product-flazz>flazz sering tidak terbaca naik transjakarta</product-flazz>

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

Isi flazz bca susah amat

<product-flazz>Isi flazz susah amat</product-flazz>

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

<product-flazz>top up flazz susah banget dan mengecewakan</product-flazz>

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

Flazz BCA enggak bisa isi di Alfamart

<product-flazz>Flazz enggak bisa isi</product-flazz>

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

Produk perbankan BCA keren banget

<product-general>Produk perbankan keren banget</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:

BCA kalau mengelurakan produk baru kayaknya enggak niat

<product-general>produk enggak niat</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:

produk digital BCA sekarang banyak masalah

<product-general>produk digital banyak masalah</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:

Produk digital BCA paling pas buat milenial

<product-general>Produk digital paling pas buat milenial</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:

Produk pembiayaan BCA paling laris di Indonesia

<product-general>Produk pembiayaan paling laris di Indonesia</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:

BCA paling bagus untuk produk perbankan di Asia

<product-general>paling bagus produk perbankan</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:

Bertransaksi dengan produk BCA memang paling menyenangkan

<product-general>Bertransaksi produk paling menyenangkan</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:

Soal keamanan, produk perbankan BCA juara pokoknya

<product-general>keamanan produk perbankan juara</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 menyesal memilih produk perbankan dari BCA

<product-general>Tidak menyesal memilih produk perbankan</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:

Ribet banget urusan sama produk BCA

<product-general>Ribet banget 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:

kantor cabang BCA di luar jakarta buruk banget pelayanannya

<service-kantor cabang>kantor cabang buruk banget pelayanannya</service-kantor cabang>

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

pelayanan kantor cabang BCA tumben ribet banget

<service-kantor cabang>pelayanan kantor cabang ribet banget</service-kantor cabang>

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

Kantor cabang BCA rawamangun fasilitasnya lengkap

<service-kantor cabang>Kantor cabang rawamangun fasilitasnya lengkap</service-kantor cabang>

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

Kantor cabang BCA yang di jalan sudirman pelayanannya kacau

<service-kantor cabang>Kantor cabang yang di jalan sudirman pelayanannya kacau</service-kantor cabang>

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

serba ribet transaksi di kantor cabang bca surabaya

<service-kantor cabang>serba ribet transaksi kantor cabang surabaya</service-kantor cabang>

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

Di Kantor cabang BCA tidak bisa mengurus atm hilang

<service-kantor cabang>Kantor cabang tidak bisa mengurus atm hilang</service-kantor cabang>

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

Kantor cabang BCA di Maranatha terlalu cepat tutup pelayanannya

<service-kantor cabang>Kantor cabang di Maranatha terlalu cepat tutup pelayanannya</service-kantor cabang>

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

Di Kantor cabang BCA tidak bisa mengurus penggantian buku tabungan yang rusak

<service-kantor cabang>Kantor cabang tidak bisa penggantian buku tabungan</service-kantor cabang>

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

<service-kantor cabang>transaksi ribet banget kantor cabang kuningan</service-kantor cabang>

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

Antrenya super panjang di Kantor Cabang BCA Serang

<service-kantor cabang>Antrenya super panjang Kantor Cabang Serang</service-kantor cabang>

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