text
stringlengths 18
378
| output
stringlengths 23
408
| prompt
stringclasses 1
value |
|---|---|---|
@ID_BCA menunggu di bca prioritas lama banget , 1 jam belum beres-beres
|
<service-prioritas>prioritas lama banget , 1 jam belum beres-beres</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@ BCA Prioritas .Lama sekali ini menunggu nya .
|
<service-prioritas>Prioritas Lama sekali ini menunggu</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Ke BCA Prioritas itu enak , bisa mencomot susu , permen sampai puas apalagi kalau menunggu nya lama , banyak pemandangan
|
<service-prioritas>Prioritas enak</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
BCA prioritas lama sekali .Kata nya " prioritas " tetapi costumer service - nya cuma sebiji .1 jam sudah
|
<service-prioritas>prioritas lama sekali costumer service cuma sebiji</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bank BCA prioritas lama pencairan nya !
|
<service-prioritas>prioritas lama pencairan</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Ini pegawai BCA Prioritas menghitung duit sambil menonton gosip di TV .Belum lagi pakai bengong , lama ya mbak kerja nya .
|
<service-prioritas>pegawai Prioritas menghitung duit sambil menonton gosip di TV . Belum lagi pakai bengong , lama ya mbak kerja nya</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Di teller BCA prioritas kagak ada beda nya .mengantre nya lama juga bzz
|
<service-prioritas>teller prioritas mengantre nya lama</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
BCA Prioritas tomang enggak bikin cepat transaksi .Bikin lama iya karena kemewahan nya .Hahahaha
|
<service-prioritas>Prioritas enggak bikin cepat transaksi Bikin lama iya karena kemewahan nya</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Huft , gila ya BCA prioritas mengantre nya lebih lama .Grr .
|
<service-prioritas>prioritas mengantre lebih lama</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Walau sudah Prioritas tetap saja antre nya lama banget .memang BCA ( Bank Capek Antre )
|
<service-prioritas>Prioritas antre lama banget</service-prioritas>
<service-general>Bank Capek Antre</service-general>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
mengantre bca lama banget .Sudah masuk prioritas tetap saja kayak ular antrean nya
|
<service-general>mengantre lama banget</service-general>
<service-prioritas>prioritas kayak ular antrean</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Nyokap mengamuk lagi di BCA , BCA juga resek banget !Prioritas nya masa mengantre lama banget .Sampah .
|
<general>resek banget</general>
<service-prioritas>Prioritas mengantre lama banget</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bca prioritas percuma juga lama juga menunggu nya :(
|
<service-prioritas>prioritas percuma juga lama menunggu</service-prioritas>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Suka banget Lihat iklan solusi bisnis bca , bukan karena dahulu pernah kerja di sana ya !tetapi memang pesan nya itu mengena banget pada penonton :)
|
<general-iklan>Suka banget iklan solusi bisnis pesan mengena banget pada penonton</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan " solusi BCA " sangat bagus !
|
<general-iklan>Iklan sangat bagus</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bni menyebalkan .Aku komplain penipuan sama cc enggak ditanggapi dengan baik
|
<general>menyebalkan</general>
<service-general>komplain penipuan sama cc enggak ditanggapi dengan baik</service-general>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bca tabungan nya Biaya admin nya mahal .
|
<product-simpanan>tabungan Biaya admin mahal</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bca bisa ditarik sampai habis , tetapi biaya admin bulanan nya mahal kalau yang biasa ( bukan yang bca Xpresi ) .
|
<product-simpanan>bisa ditarik sampai habis biaya admin mahal kalau yang biasa</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
cimb tabungan ku : edc / atm di mana-mana , enggak ada biaya admin
|
<product-simpanan>tabungan ku enggak ada biaya admin</product-simpanan>
<facility-EDC>edc di mana-mana</facility-EDC>
<facility-atm>atm di mana-mana</facility-atm>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
bca gold : edc / atm di mana-mana , biaya admin mahal ( 17.000 )
|
<product-simpanan>gold biaya admin mahal</product-simpanan>
<facility-EDC>edc di mana-mana</facility-EDC>
<facility-atm>atm di mana-mana</facility-atm>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
BCA karena dari kampus dan mudah ditemukan di mana-mana tetapi mahal nih biaya admin nya
|
<general>mudah ditemukan di mana-mana</general>
<product-simpanan>mahal biaya admin</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@HaloBCA Kita bayar biaya admin supermahal .Bank dengan biaya admin termahal di Indonesia kok kerjaan nya eror melulu
|
<product-simpanan>biaya admin supermahal</product-simpanan>
<general>kerjaan nya eror melulu</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:
|
pernah di Bangkok tarik di atm AEON pakai debit BCA enggak kena biaya admin , tetapi sedikit lebih mahal daripada tukar uang di tempat penukaran uang Jakarta Barat .
|
<product-kartu debit>tarik di atm AEON debit enggak kena biaya admin</product-kartu debit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Tetapi biaya admin paling mahal dipegang BCA admin paling gede , bunga nya masih dipotong pajak lagi wkwkwk
|
<product-simpanan>biaya admin paling mahal bunga masih dipotong pajak lagi</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
bca , kelebihan nya bisa dipakai di asia kekurangan nya biaya admin mahal
|
<general>bisa dipakai di asia</general>
<product-simpanan>biaya admin mahal</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Istigfar deh sama BCA isi pulsa lewat ATM saja kena biaya admin sudah begitu lebih mahal lagi daripada beli di konter
|
<facility-atm>isi pulsa ATM kena biaya admin sudah begitu lebih mahal lagi daripada beli di konter</facility-atm>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pembelian pulsa @Telkomsel di ATM BCA mahal karena biaya admin enggak jelas @HaloBCA
|
<facility-atm>Pembelian pulsa ATM mahal biaya admin enggak jelas</facility-atm>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Transfer pulsa di ATM BCA sekarang mahal ada biaya admin @HaloBCA
|
<facility-atm>Transfer pulsa ATM mahal ada biaya admin</facility-atm>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BizGuideBCA biaya admin bulanan BCA kok sekarang mahal banget .dari 13 ribu sekarang 17 ribu .
|
<product-simpanan>biaya admin mahal banget</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pantas saja bos gue enggak mau transfer bukan sesama BCA orang biaya admin nya mahal banget - _ -
|
<facility-e-channel>transfer bukan sesama biaya admin nya mahal banget</facility-e-channel>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Buset BCA biaya admin nya mahal banget , bank lain transfer bukan sesama cuman kena biaya admin 5 ribu atau enggak 10 ribu tetapi BCA sampai 17 ribu gila
|
<facility-e-channel>biaya admin nya mahal banget transfer bukan sesama biaya admin 5 ribu atau enggak 10 ribu sampai 17 ribu gila</facility-e-channel>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Biaya admin bulanan BCA mahal banget !
|
<product-simpanan>Biaya admin mahal banget</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
aduh bca mahal biaya admin .Ini saja mau aku tutup rekening : 3 "
|
<product-simpanan>mahal biaya admin</product-simpanan>
<product-kartu kredit>mandiricard naik limit ribet</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Mandiri kampungan ah , ribet banget limit multipayment cuma 5 juta , bikin platinum biaya admin kayak mau naik haji , mana saldo minimal 100 ribu !
|
<general>kampungan</general>
<product-simpanan>ribet banget limit multipayment cuma 5 juta platinum biaya admin kayak mau naik haji saldo minimal 100 ribu</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
sumpah deh , mandiri ribet amat !Mau setor di atas 100 juta harus mengisi formulir .Kemarin jam 2 setor , ditolak , karena mereka sudah overlimit duit nya .Apa
|
<general>ribet amat</general>
<service-teller>setor di atas 100 juta harus mengisi formulir setor ditolak , karena mereka sudah overlimit duit nya</service-teller>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 3 Tahun lebih menjadi nasabah kartu kredit @MNCBank namun SUSAH sekali naik limit padahal histori pemakaian kartu kredit saya selalu bagus
|
<product-kartu kredit>kartu kredit SUSAH sekali naik limit</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
MENYESAL menggunakan CC @BNISyariah bunga besar susah naik limit dan anjing
|
<product-kartu kredit>CC bunga besar susah naik limit anjing</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Saya pakai @KartuKreditBCA 4 tahun susah banget naik limit nya .masih 3 juta .sedangkan CC saya yang lain rata-rata limit 7 -- 15 juta , pembayaran saya lancar
|
<product-kartu kredit>KartuKreditBCA susah banget naik limit</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Susah benar ya minta naik limit cc di @halobca jadi nasabah setia kayak enggak ada guna nya , bayar enggak pernah telat juga .
|
<product-kartu kredit>Susah benar naik limit cc</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
iklan BNI versi asian games juga keren banget
|
<general-iklan>iklan versi asian games keren banget</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Sumpah iklan BNI yang baru keren parah .Iklan Indonesia memang sudah saat nya kreatif dan inspiratif sih .
|
<general-iklan>iklan keren parah</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan komersial Mandiri Prioritas ini keren .Cakap .Sudah lama enggak lihat iklan bank keren semenjak BNI dahulu .
|
<general-iklan>Iklan Prioritas keren . Cakap iklan bank keren</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan BNI keren .Semoga entar anak gue enggak begitu
|
<general-iklan>Iklan keren</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
iklan BNI sumpah keren menyentuh pula : " )
|
<general-iklan>iklan sumpah keren menyentuh pula iklan keren banget</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan BNI yang baru keren banget .gemas sekali apalagi si @Jefan_Nathanio senang ya lihat nya
|
<general-iklan>Iklan keren banget</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan BNI 46 keren !Ada unsur solidaritas beragama nya
|
<general-iklan>Iklan keren ! Ada unsur solidaritas beragama nya</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
anjing merinding melihat iklan Bank BNI yang tema nya lebaran .KEREN !
|
<general-iklan>iklan lebaran KEREN</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Wow !Iklan BNI keren ya .Pemaknaan baru tentang pahlawan .Ide bagus !
|
<general-iklan>Iklan keren ya . Pemaknaan baru tentang pahlawan . Ide bagus</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan bank BNI 46 keren sekali .Inspiratif !Siapa kreatif nya ?
|
<general-iklan>Iklan keren sekali . Inspiratif</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan BNI keren .Narasi nya TOP .Semangat 46 !
|
<general-iklan>Iklan keren Narasi TOP</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan BNI keren chelsea payment card - nya , untung baru buka rekening haha belum dapat kartu nya sebentar lagi juga jadi : D
|
<general-iklan>Iklan keren</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Sumpah iklan bank BNI keren
|
<general-iklan>iklan bank BNI keren</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan Bank BNI keren banget .Itu kisah Nyata di Bali .
|
<general-iklan>Iklan keren banget</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
keren nih iklan bni 46 yang indah nya perbedaan
|
<general-iklan>keren iklan yang indah nya perbedaan</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Perbedaan bukan buat dibenci , keren iklan BNI mantap !
|
<general-iklan>keren iklan mantap</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan BNI ini keren sekali sumpah , toleransi antarumat beragama di Indonesia , jadi terharu :')
|
<general-iklan>Iklan keren sekali sumpah</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bagus , ya .slogan iklan lebaran BNI : Keikhlasan berkaca , adalah awal kemenangan sejati .
|
<general-iklan>Bagus slogan iklan</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iklan lebaran punya BNI bagus banget .menangis masa lihat nya .: " (
|
<general-iklan>Iklan lebaran bagus banget . menangis masa lihat nya Iklan bagus</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Mandiri bagus juga iklan kemerdekaan nya ,
|
<general-iklan>bagus iklan kemerdekaan</general-iklan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@mandiricare @bankmandiri mandiri di soekarno hatta bandung susah banget ditelepon .Dari kemarin entah sudah berapa kali .KTA saya kok didebit 2x dari rekening
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<service-customer center>mandiricare susah banget ditelepon</service-customer center>
<product-pinjaman>KTA didebit 2x dari rekening</product-pinjaman>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@mandiricare Yang terhormat Mandiri , untuk peminjaman KTA Mandiri Payroll susah nya minta ampun .
|
<product-pinjaman>peminjaman KTA Mandiri Payroll susah nya minta ampun</product-pinjaman>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
mandiri sekarang jadi ribet ya ,
|
<general>ribet</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:
|
@mandiri_info admin KTA kok rumit dan ribet .Tidak simpel .
|
<product-pinjaman>KTA rumit dan ribet . Tidak simpel</product-pinjaman>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNISyariah BNI syariah prosedur ajukan KTA susah / bunga nya tinggi
|
<product-pinjaman>prosedur ajukan KTA susah bunga tinggi</product-pinjaman>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Saya mau tutup kartu kredit BNI .Susah .Berbelit-belit prosedur nya .Minta ampun .
|
<product-kartu kredit>tutup kartu kredit Susah . Berbelit-belit prosedur nya . Minta ampun</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pelayanan Kartu kredit Bank Mega @BankMegaID harus belajar dari bank BCA @KartuKreditBCA , Mandiri @mandiricard .Masa ada tagihan biaya informasi transaksi , mau tutup kartu susah , minta ditelepon enggak dibantu padahal bank BNI , BCA Mandiri mau menelepon nasabah dan menyediakan layanan surel juga
|
<product-kartu kredit>Kartu kredit ada tagihan biaya informasi transaksi tutup kartu susah ditelepon enggak dibantu</product-kartu kredit>
<service-general>mau menelepon nasabah menyediakan layanan surel</service-general>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Tutup BNI karena ADA SAJA TAWARAN enggak PENTING yang SUSAH BANGET DIBILANG ENGGAKNYA .
|
<general>ADA SAJA TAWARAN enggak PENTING yang SUSAH BANGET DIBILANG ENGGAKNYA</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:
|
Tutup Kartu Kredit BNI Susah - Saya pemegang kartu kredit BNI
|
<product-kartu kredit>Tutup Kartu Kredit Susah</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bangsat BNI nih , aku mengaktifkan kartu kredit maka timbul tagihan iuran tahunan .Bangkai lalu .Giliran ditelepon mau tutup kartu malah ribet
|
<general>Bangsat</general>
<product-kartu kredit>mengaktifkan kartu kredit timbul tagihan iuran tahunan tutup kartu ribet</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Tutup buka rekening ini kayak gali lubang tutup lubang *pengin pindah ke BCA tetapi ribet*
|
<general>ribet</general>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Ribet gila nih CC BCA .Kelebihan pembayaran terus mau tutup kartu malah ditolak .geblek !
|
<product-kartu kredit>Ribet gila CC tutup kartu ditolak . geblek</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bca ribet banget .mengurusi tutup rekening juga ribet banget
|
<general>ribet banget</general>
<product-simpanan>tutup rekening ribet banget</product-simpanan>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pas telepon call center - nya malah nada nya naik padahal kan gue mau sanggah transfer cc , pengin cepat tutup kartu saja .Bri ribet dan aneh @kontakBRI
|
<service-customer center>call center nada nya naik</service-customer center>
<general>ribet dan aneh</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:
|
Aneh saja sih , masa mau tutup kartu saja harus menunggu 14 hari .#BRI_ribet @BANKBRI_ID @kontakBRI
|
<product-kartu kredit>tutup kartu harus menunggu 14 hari</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Enggak cuma urusan CC , pelunasan kredit juga dibikin ribet nya buset deh tutup kartu kredit BRI - nya ribet urusan sama mereka
|
<product-kartu kredit>pelunasan kredit ribet nya buset tutup kartu kredit ribet urusan sama mereka</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Kesimpulan nya ya tadi , tutup kartu kredit BRI - nya mas , ribet urusan sama mereka , banyak bank lain yang simpel dan membantu proses
|
<product-kartu kredit>tutup kartu kredit ribet urusan sama mereka</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
mau tutup kartu kredit BRI kok ribet
|
<product-kartu kredit>tutup kartu kredit ribet</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@bankmandiri Aku makanya semua jasa mandiri kartu kredit tutup , rekening pribadi ya masih ada isi nya dikit .Rekening kantor pindah ke bank lain .Rekening yayasan juga pindah .Ribet banget asli .
|
<general>Ribet banget asli</general>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Mau tutup kartu kredit bank mandiri saja ribet banget .pakai dioper-oper , pulsa saya habis nih grr .kesal .
|
<product-kartu kredit>tutup kartu kredit ribet banget . pakai dioper-oper , pulsa saya habis nih grr . kesal</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Tutup kartu kredit mandiri kok susah banget sih .Ribet banget .
|
<product-kartu kredit>Tutup kartu kredit susah banget Ribet banget</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Iya permata cc mah ribet kalau mau tutup kartu
|
<product-kartu kredit>cc ribet tutup kartu</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@danamon mau ganti nomor telepon genggam di data CC saja ribet minta ampun , enggak ada solusi tutup CC
|
<product-kartu kredit>ganti nomor telepon genggam di data CC ribet minta ampun</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Komplain ke Mandiri : minta kirim lagi malah kena biaya & ribet lagi urusan nya .Ya sudah tutup saja , enggak perlu amat kok .Tembusan : @mandiri_info
|
<product-kartu kredit>kena biaya & ribet lagi urusan nya</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Ribet pake cc mandiri , tutup saja ah .KAPOK
|
<product-kartu kredit>Ribet cc KAPOK</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
sudah gue tutup juga dik , malah ribet ada 2 cc mandiri
|
<product-kartu kredit>ribet ada 2 cc</product-kartu kredit>
<product-asuransi>mandiri</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:
|
@HelloDanamon Mau tutup CC Danamon .Coba hubungi 1500090 tetapi susah banget .
|
<product-kartu kredit>tutup CC Coba hubungi 1500090 tetapi susah banget</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@CIMBNiaga saya lagi kesal sama CIMB Niaga , mau tutup kartu saja susah dan harus telepon berkali-kali ke 14041 .Layanan macam apa sih kalian ini
|
<general>kesal</general>
<product-kartu kredit>tutup kartu susah dan harus telepon berkali-kali ke 14041</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@CIMB_Assists kecewa dengan CIMB Niaga Kartu Kredit , mau tutup kartu kredit susah sekali , sudah kartu Rusak permintaan penggantian tidak dilakukan
|
<product-kartu kredit>kecewa Kartu Kredit tutup kartu kredit susah sekali kartu Rusak permintaan penggantian tidak dilakukan</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
CIMB Niaga sial !Mau tutup kartu saja dibikin susah , padahal tagihan sudah NOL !
|
<general>sial</general>
<product-kartu kredit>tutup kartu dibikin susah</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
aduh cimb niaga kok ribet ya , masa harus pulang dahylu ke tasikmalaya .
|
<general>ribet</general>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
saya tutup CC Niaga gara-gara proses nya ribet mas .CC lain masih banyak .Maaf ya @CIMB_Assist
|
<product-kartu kredit>CC proses nya ribet</product-kartu kredit>
|
Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
simpan barang atau dokumen berharga Anda di tempat yang aman dan terpercaya, seperti Safe Deposit Box dari BCA.
|
<facility-deposit box>aman dan terpercaya Safe 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:
|
gampang banget pakai safe deposit box bca. suka aku itu
|
<facility-deposit box>gampang banget safe deposit box suka</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:
|
safe deposit box bca murah meriah. bangga gue sama bca
|
<facility-deposit box>safe deposit box murah meriah</facility-deposit box>
<general>bangga</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:
|
aman banget menyimpan emas batangan di deposit box bca
|
<facility-deposit box>aman banget menyimpan emas batangan 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:
|
deposit box bca enggak aman buat duit-duit yang disimpan oleh nasabah.
|
<facility-deposit box>deposit box enggak aman buat duit-duit yang disimpan oleh nasabah</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:
|
boks sudah pada karatan, jadi gue susah masukan kuncinya. besok-besok harus ada pemeliharaan buat deposit box dong bca
|
<facility-deposit box>boks karatan susah masukan kuncinya 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:
|
kurang minyak kali ini lubang kunci deposit box bca di sini. bunyinya kayak suara lucinta luna
|
<facility-deposit box>kurang minyak lubang kunci deposit box bunyinya kayak suara lucinta luna</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:
|
ribet banget pakai deposit box bca. segala harus isi informasi kunjungan
|
<facility-deposit box>ribet banget 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:
|
BCA safe deposit box-nya atau SDB-nya kokoh banget karena terbuat dari baja.
|
<facility-deposit box>safe deposit box-nya kokoh banget karena terbuat dari baja</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:
|
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