text
stringlengths 18
378
| output
stringlengths 23
408
| prompt
stringclasses 1
value |
|---|---|---|
paling murah kalau sewa deposit box ke bca | <facility-deposit box>paling murah sewa deposit box</facility-deposit box> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Senangnya bisa menggunakan fasilitas BCA. | <facility-general>Senangnya fasilitas</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Fasilitas BCA semakin hari semakin membaik. | <facility-general>Fasilitas semakin hari semakin membaik</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Untuk bank sebesar BCA, fasilitasnya masih di bawah bank lain. | <facility-general>fasilitasnya masih di bawah bank lain</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Fasilitas BCA Dago lengkap juga ya. | <facility-general>Fasilitas lengkap</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Payah sekali fasilitas BCA KPC Kebon Sirih. | <facility-general>Payah sekali fasilitas</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pelayanan dan fasilitas di BCA Maranatha luar biasa bagus. | <service-general>Pelayanan luar biasa bagus</service-general>
<facility-general>fasilitas luar biasa bagus</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
fasilitas BCA di mana-mana memang selalu yang paling bagus ya. | <facility-general>fasilitas selalu yang paling bagus</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
AC di BCA KCP Cibadak tidak dingin, payah. | <facility-general>AC tidak dingin , payah</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Selalu merasa terbantu dengan segala fasilitas yang diberikan oleh BCA kepada nasabah. | <facility-general>Selalu merasa terbantu fasilitas</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Fasilitas BCA payah banget sumpah! | <facility-general>Fasilitas payah banget sumpah</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
giro yang disetor hari ini tidak bisa cair di bca | <product-giro>giro tidak bisa cair</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
susah banget urus giro bca kemarin | <product-giro>susah banget giro</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
pencairan giro saja di BCA lamanya minta ampun | <product-giro>pencairan giro lamanya minta ampun</product-giro>
<product-asuransi>BCA</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
dibuat kesal hari ini karena mengurus giro di bank BCA ribet | <product-giro>giro ribet</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
giro di BCA memang bikin tenang dan aman | <product-giro>giro tenang dan aman</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
susah kalau bayar pakai giro bca | <product-giro>susah bayar giro</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 pencairan giro di BCA Margonda sangat buruk | <product-giro>pencairan sangat buruk</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
kirim lewat giro BCA saja, gampang mengurusnya | <product-giro>kirim giro gampang</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pembukaan giro di bca sangat enak dan mudah ternyata | <product-giro>Pembukaan giro sangat enak dan mudah</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
paling sebal kalau harus urus giro lewat BCA yang lelet pencairannya | <product-giro>sebal giro lelet pencairannya</product-giro> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
agak susah kalau mau buka rekening deposito bca lewat aplikasi | <product-deposito>agak susah buka rekening deposito</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
pembukaan rekening deposito BCA tidak mudah dan banyak syaratnya | <product-deposito>pembukaan rekening deposito tidak mudah banyak syaratnya</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Membuat rekening deposito bca semakin mudah sekarang | <product-deposito>Membuat rekening deposito semakin mudah</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
deposito BCA akan membantu anda memudahkan rencana jangka panjang keluarga | <product-deposito>deposito membantu anda memudahkan rencana jangka panjang keluarga</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 tahunan deposito bca mahal | <product-deposito>Bunga tahunan deposito mahal</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 menaikkan bunga deposito lagi jadi semakin mahal | <product-deposito>menaikkan bunga deposito semakin mahal</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
saya membuka rekening deposito BCA tetapi prosedurnya ribet | <product-deposito>membuka rekening deposito prosedurnya ribet</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
pembukaan rekening deposito bca payah hanya bisa di kantor cabang | <product-deposito>pembukaan rekening deposito payah</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
enak banget pelayanan buka deposito di bca pasteur | <product-deposito>enak banget buka deposito</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
setoran awal deposito bca paling murah | <product-deposito>setoran awal deposito paling murah</product-deposito> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
promo bank BCA sekarang susah di dapat | <general-promo>promo susah</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
promo BCA di KFC tidak sesuai kenyataan | <general-promo>promo tidak sesuai kenyataan</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
tumben bca enggak pelit promo bulan ini | <general-promo>enggak pelit promo</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 bca dapat promo potongan harga 5 persen untuk pembelian tiket konser | <general-promo>dapat promo potongan harga 5 persen untuk pembelian tiket konser</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 kasih promo tidak banyak alias pelit | <general-promo>promo tidak banyak alias pelit</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 sedang kasih promo bagi yang membuka rekening xpresi sampai akhir bulan ini | <general-promo>sedang kasih promo bagi yang membuka rekening xpresi sampai akhir bulan ini</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Promo BCA potongan harga 25% tidak bisa dipakai | <general-promo>Promo tidak bisa dipakai</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 tidak jelas kasih informasi promo | <general-promo>tidak jelas informasi promo</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 curang, info promo tidak diberikan ke semua nasabah | <general>curang</general>
<general-promo>promo tidak diberikan ke semua nasabah</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
pelitnya bca dalam hal promo | <general-promo>pelitnya promo</general-promo> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
sudah pasti ribet kalau urusan payroll di BCA | <facility-payroll>ribet payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Enggak pernah benar mengurus payroll di BCA | <facility-payroll>Enggak pernah benar payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Begini ribet deh kalau payroll perusahaan pakai BCA | <facility-payroll>ribet payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
fasilitas payroll dari BCA sudah paling rumit prosedurnya | <facility-payroll>payroll paling rumit prosedurnya</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Paling nyaman kalau payroll lewat BCA | <facility-payroll>Paling nyaman payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pengelolaan payroll di BCA paling mantap selama yang gue alami | <facility-payroll>Pengelolaan payroll paling mantap</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Enggak ada yang paling susah selain urusan payroll di BCA | <facility-payroll>paling susah payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pengajuan payroll perusahaan pakai BCA ribetnya minta ampun | <facility-payroll>Pengajuan payroll ribetnya minta ampun</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Sistem payroll BCA bulan ini bermasalah | <facility-payroll>Sistem payroll bermasalah</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
gue sudah paling nyaman kalau urusan payroll pakai BCA | <facility-payroll>paling nyaman payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pengajuan pembuatan payroll di BCA lama sekali prosesnya | <facility-payroll>pembuatan payroll lama sekali prosesnya</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Terlalu banyak aturan ingin buka payroll lewat BCA | <facility-payroll>Terlalu banyak aturan buka payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 banget kalau mau buka payroll BCA | <facility-payroll>Sulit banget buka payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
sistem penggajian pakai payroll bca saja mudah dan aman | <facility-payroll>sistem penggajian payroll mudah dan aman</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
susah banget mau urus payroll bca | <facility-payroll>susah banget payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
layanan payroll bca paling top pokoknya | <facility-payroll>payroll paling top</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
belum pernah kecewa kalau payroll pakai bca | <facility-payroll>belum pernah kecewa payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
BCA memang paling ahli kalau urusan payroll | <facility-payroll>paling ahli payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 itu juara untuk payroll perusahaan | <facility-payroll>juara payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
ribetnya bukan main sistem penggajian pakai payroll bank bca | <facility-payroll>ribetnya sistem penggajian payroll</facility-payroll> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Asuransi BCA buruk pelayanannya | <product-asuransi>Asuransi buruk pelayanannya</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
petugas asuransi BCA tidak ramah | <product-asuransi>petugas asuransi tidak ramah</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
bayar asuransi BCA gagal terus | <product-asuransi>bayar asuransi gagal terus</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
premi asuransi bca mahal | <product-asuransi>premi asuransi mahal</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 mengajukan asuransi bca tetapi syaratnya susah | <product-asuransi>mengajukan asuransi syaratnya susah</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
banyak prosedur yang ribet harus dipenuhi untuk daftar asuransi BCA | <product-asuransi>banyak prosedur yang ribet daftar asuransi</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 menggunakan asuransi BCA | <product-asuransi>Tidak menyesal asuransi</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
payah banget klaim asuransi BCA | <product-asuransi>payah banget klaim asuransi</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
premi bulanan asuransi bca murah | <product-asuransi>premi asuransi murah</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 asuransi bca sungguh enak dan nyaman | <product-asuransi>asuransi enak dan nyaman</product-asuransi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Kredit kendaraan bermotor dari BCA dendanya mahal | <product-KKB>Kredit kendaraan bermotor dendanya mahal</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Cicilan mobil pakai KKB BCA saja, murah dan aman | <product-KKB>Cicilan mobil KKB murah dan aman</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Prosedur memakai KKB BCA sulitnya minta ampun | <product-KKB>Prosedur KKB sulitnya minta ampun</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Angsuran kredit kendaraan bermotor BCA rendah | <product-KKB>Angsuran kredit kendaraan bermotor rendah</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Nyaman banget kalau beli mobil pakai KKB dari BCA | <product-KKB>Nyaman banget beli mobil KKB</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Ternyata ribet mau mengurus kredit motor pakai KKB BCA | <product-KKB>ribet kredit motor KKB</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
KKB BCA sekarang semakin mudah | <product-KKB>KKB semakin mudah</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
kredit motor pakai layanan KKB BCA susah banget | <product-KKB>kredit motor KKB susah banget</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
KKB BCA sekarang banyak yang pakai | <product-KKB>KKB banyak yang pakai</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 KKB BCA banyak kasih promo | <product-KKB>KKB banyak promo</product-KKB> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Lama banget cuma mau mengurus KMK di BCA | <product-KMK>Lama banget KMK</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
KMK BCA syaratnya banyak banget | <product-KMK>KMK syaratnya banyak banget</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Mengajukan KMK di BCA ternyata ribet prosedurnya | <product-KMK>Mengajukan KMK ribet prosedurnya</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 KMK BCA lebih murah sekarang | <product-KMK>Bunga KMK murah</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Kemarin urus KMK di BCA yang ternyata mudah dan cepat | <product-KMK>KMK mudah dan cepat</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Sangat mudah mengajukan KMK di BCA | <product-KMK>Sangat mudah mengajukan KMK</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
KMK BCA cepat banget pencairannya | <product-KMK>KMK cepat banget pencairannya</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Kredit Modal Kerja BCA bunganya mahal parah | <product-KMK>Kredit Modal Kerja bunganya mahal parah</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 mengajukan KMK di BCA | <product-KMK>Ribet banget mengajukan KMK</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 tawarkan bunga rendah untuk pengajuan Kredit Modal Kerja | <product-KMK>tawarkan bunga rendah pengajuan Kredit Modal Kerja</product-KMK> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pencairan KUR di BCA lama banget | <product-KUR>Pencairan KUR lama banget</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:
|
Syarat pengajuan KUR di BCA panjang dan berbelit | <product-KUR>Syarat pengajuan KUR panjang dan berbelit</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:
|
aturan KUR BCA tidak memudahkan rakyat kecil | <product-KUR>aturan KUR tidak memudahkan rakyat kecil</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:
|
Ribet banget penuhi persyaratan KUR lewat BCA | <product-KUR>Ribet banget persyaratan KUR</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:
|
KUR BCA bunganya membebankan rakyat kecil | <product-KUR>KUR bunganya membebankan rakyat kecil</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:
|
Saya klaim KUR di BCA rumitnya sangat sekali | <product-KUR>klaim KUR rumitnya sangat sekali</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:
|
Saya sudah ambil KUR BCA yang prosesnya cepat dan tidak ribet | <product-KUR>KUR prosesnya cepat dan tidak ribet</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:
|
Terima kasih BCA yang membantu mempermudah mengambil KUR di BCA | <product-KUR>mempermudah mengambil KUR</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:
|
Usaha saya terbantu karena mengurus KUR di BCA sangat cepat dan nyaman | <product-KUR>mengurus KUR sangat cepat dan nyaman</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:
|