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stringlengths 18
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@BNICustomerCare @Bni Benarkan itu aplikasi selular nya , Banyak yang mengasih ulasan jelek tetapi didiamkan saja , sangat jauh dari aplikasi seluler bank lain | <facility-aplikasi>aplikasi selular Banyak yang mengasih ulasan jelek tetapi didiamkan saja</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Tetapi mobile banking - nya paling jelek , mandiri dan bni jauh lebih baik | <facility-aplikasi>mobile banking jauh lebih baik</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
memuat melulu mau top up GoPay via BNI Mobile . | <facility-aplikasi>memuat melulu top up GoPay Mobile</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Hampir semua aplikasi selular perbankan di Indonesia tampilan nya jelek banget , | <facility-aplikasi>aplikasi selular tampilan jelek banget</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Jenius sudah paling asyik memakai nya | <product-e-money>Jenius paling asyik memakai nya</product-e-money> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNICustomerCare bni mobile banking jelek banget ganti telepon genggam harus ke kantor cabang lagi parah | <facility-aplikasi>mobile banking jelek banget ganti telepon genggam harus ke kantor cabang lagi parah</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
BNI contoh itu BCA dan Mandiri .@HaloBCA dan bank @mandiricare ganti telepon genggam gampang masuk lagi | <facility-aplikasi>ganti telepon genggam gampang masuk lagi</facility-aplikasi>
<facility-BCA Mobile>ganti telepon genggam gampang masuk lagi</facility-BCA Mobile> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
mending hapus aplikasi bni mobile banking kalau begini . | <facility-aplikasi>mending hapus mobile banking</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bni mobile memang begitu .Jelek banget .Gue saja mencopot .Berharap diperbaiki biar kayak bank-bank lain begitu | <facility-aplikasi>mobile Jelek banget</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
tolong mobile banking aplikasi nya diperbaiki dong , JELEK BANGET .Tiap habis keluar aplikasi nya minta setel ulang , dan berkali-kali gagal ! | <facility-BCA Mobile>mobile banking JELEK BANGET keluar aplikasi minta setel ulang , dan berkali-kali gagal</facility-BCA Mobile> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Kepada @BNI @BNICustomerCare pengisian pulsa melalui BNI mobile sangat buruk sekali . | <facility-aplikasi>pengisian pulsa BNI mobile sangat buruk sekali</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNI @BNICustomerCare sangat buruk sekali pelayanan mobile banking - nya , akan saya laporkan ke YLKI , koneksi terputus tetapi transaksi berhasil , sangat kecewa | <facility-aplikasi>sangat buruk sekali pelayanan mobile banking koneksi terputus tetapi transaksi berhasil , sangat kecewa</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNI mobile banking kalian kapan benar nya ?Kok sekarang buruk sekali kinerja aplikasi nya .Saya sudah 2 bulan bikin komplain enggak benar-benar . | <facility-aplikasi>mobile banking buruk sekali kinerja aplikasi</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNI pelayanan mobile banking yang sangat buruk , koneksi terputus tetapi transaksi berhasil | <facility-aplikasi>pelayanan mobile banking sangat buruk</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Aplikasi BNI mobile sangat-sangat buruk . | <facility-aplikasi>mobile sangat-sangat buruk</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNI coba nih keluhan mobile banking bni yang buruk segera diperbaiki aplikasi nya dengan tim IT profesional . | <facility-aplikasi>mobile banking buruk</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Buat layanan e - banking ini bank bca juga enggak kalah bagus .hampir belum pernah gue mengalami gangguan sistem , buat autentikasi dia pakai token | <facility-e-channel>layanan e - banking enggak kalah bagus belum pernah gue mengalami gangguan sistem autentikasi pakai token</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:
|
@BNI fitur yang sangat membantu dan jadi favorit saya adalah pembelian token listrik , karena bisa 24 jam #BNIMobileBanking #FiturFavorite | <facility-aplikasi>fitur yang sangat membantu dan jadi favorit pembelian token listrik BNIMobileBanking</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@TipsJualOnline bca mandiri bri aplikasi M - banking nya bagus .enggak ribet pakai token | <facility-aplikasi>M - banking bagus . enggak ribet pakai token</facility-aplikasi>
<facility-m-bca>M - banking bagus . enggak ribet pakai token</facility-m-bca> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Token mandiri lebih mahal 5.000 dari bni , tetapi bentuk nya lebih bagus sama lebih nyaman dipencet . | <facility-aplikasi>Token lebih mahal 5 dari bentuk lebih bagus sama lebih nyaman dipencet</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
internet banking BRI lebih cakap dari BNI , antarmuka bagus , notifikasi lewat surel dan pakai selular token ... | <facility-aplikasi>internet banking lebih cakap dari antarmuka bagus notifikasi lewat surel pakai selular token</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Klikbca ternyata lebih bagus dari token mandiri :) ) sekarang tinggal token bni dah | <facility-aplikasi>Klikbca ternyata lebih bagus dari token</facility-aplikasi>
<facility-klikbca>Klikbca</facility-klikbca> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
BNI @BNI internet banking nantinya jadi semakin mahal dan ribet .dahulu cuma butuh internet+token , sekarang tambah butuh SMS .#WannaCry | <facility-aplikasi>internet banking semakin mahal dan ribet</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Asli e - banking BNI enggak ada yang benar .Token kata nya habis di balikpapan , mobile banking enggak bisa aktif-aktif , aplikasi sms banking - nya ribet banget hhhh | <facility-e-channel>e - banking enggak ada yang benar</facility-e-channel>
<facility-aplikasi>Token habis mobile banking enggak bisa aktif-aktif sms banking ribet banget</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNICustomerCare Pergantian Buku , ATM , dan Token BNI ribet , tidak seperti bank lain , laporan polisi tidak laku , padahal darurat . | <service-cs>Pergantian Buku , ATM , dan Token ribet</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNICustomerCare kok gangguan melulu ya server bni , mau urus e - secure dan ambil token jadi ribet enggak jelas , harus bolak-balik juga | <facility-aplikasi>gangguan melulu server e - secure token ribet enggak jelas</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
sudah , ada di cabang ruko ketapang jakarta barat / jakarta pusat .Cs - nya bilang token di sini khusus nasabah yang membuka rekening di cabang sini .Ribet banget ya | <service-kantor cabang>cabang ruko ketapang jakarta barat / jakarta pusat</service-kantor cabang>
<service-cs>Cs Ribet banget</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 sudah pakai token , pakai verifikasi sms lagi ?jadi ribet | <facility-aplikasi>sudah pakai token verifikasi sms lagi ribet</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@amasna yang KEREN itu aplikasi CIMB niaga .Simpel SMS token enggak ribet kayak BCA Mandiri atau BNI , dan tetap aman . | <facility-aplikasi>KEREN aplikasi Simpel SMS token enggak ribet</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Anjing ribet banget pakai token BRI harus ada pulsa nya , mendingan BNI pakai token e - secure langsung enggak pake ribet | <facility-aplikasi>Anjing ribet banget token token e - secure langsung enggak pake ribet</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
sudah mas tadi saya beli token di bri ribet | <service-cs>beli token ribet</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
ternyata beli token gampangan di bni hehehe | <service-cs>beli token gampangan</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 ganti token @BNI46 paling mahal & ribet , jaringan internet banking nya sering bermasalah ! | <facility-aplikasi>ganti token paling mahal & ribet jaringan internet banking sering bermasalah</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Mau beli token BNI kok ribet amat ya : | | <service-cs>beli token ribet amat</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
wah keren banget dah CLICK CIMB , transaksi enggak perlu pakai token-token kayak BNI atau BCA atau Mandiri , cukup pakai mPIN , enggak ribet bawa-bawa | <facility-aplikasi>keren banget CLICK transaksi enggak perlu pakai token-token enggak ribet</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
argh .BNI ribet permintaan token harus via internet .Terus mengambil nya di BNI fatmawati lagi :( | <general>ribet</general>
<facility-aplikasi>permintaan token harus via internet</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Pelayanan @BNI Cabang Mahendradata sangat lama , CSO cuma 1 orang sedangkan yang antre sampai puluhan .sangat disayangkan .buang-buang waktu banget | <service-general>Pelayanan sangat lama</service-general>
<service-cs>CSO cuma 1 orang antre puluhan</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Antre mau ke CS Bank @BNI Cabang USU dari 14.06 sampai 15.03 belum juga dipanggil padahal antrean di depan saya hanya 3 orang , tetapi wajar karena CS yang aktif hanya 1 orang .Akhirnya saya tinggal pulang saja | <service-cs>Antre CS belum juga dipanggil padahal antrean di depan saya hanya 3 orang hanya 1 orang</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNICustomerCare Pelayanan BNI Cibabat - Cimahi sangat lama .Sudah jam 10 tetapi antrean teller baru masuk nomor 20 .Loket tidak semuanya buka .Hari ini hanya 2 dari 4 loket yang buka sehingga nasabah lama antre . | <service-general>Pelayanan sangat lama</service-general>
<service-teller>teller Loket tidak semuanya buka lama antre</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:
|
@BNI bank bni marelan .Lambat sekali pelayanan customer service .Tiap ke sana antre 10 orang pun sampai 2 jam | <service-cs>Lambat sekali pelayanan customer service</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Kayak nya perlu menambah customer service !Masa antre dari jam setengah 2 sampai jam 2.20 belum dipanggil-panggil .Lokasi : bni kupang jaya surabaya @BNI | <service-cs>customer service antre dari jam setengah 2 sampai jam 2.2 belum dipanggil-panggil</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Enak BNI , antre nya pakai nomor | <general>Enak</general>
<service-general>antre pakai nomor</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:
|
Ujian kesabaran di hari Jumat , antre di cs BNI Praya @BNI | <service-cs>Ujian kesabaran antre cs</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 dah pakai yang tahapan muda biaya admin sebulan cuman 5 ribu dan kalau mau ke teller enggak ribet antre panjang .mantap | <product-simpanan>tahapan muda biaya admin cuman 5 ribu</product-simpanan>
<service-teller>teller enggak ribet antre panjang . mantap</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:
|
Teller @BNI Kcp Depok II Tengah bisa enggak panggil sesuai antrean Masa sudah antre sejam panggilan nya sudah diacak | <service-teller>Teller antre panggilan nya sudah diacak</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:
|
mengantre di @BNI jakal km 7 jogja .Cuma antre 4 tetapi satu jam enggak kelar-kelar .CS yang disediakan cuma satu .Apa-apaan . | <service-cs>antre satu jam enggak kelar-kelar CS cuma satu</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNICustomerCare andai saja BNI cabang Cepu - blora punya ATM setor tunai .Saya dan nasabah yang lain enggak perlu antre dan buang-buang waktu kayak begini | <service-kantor cabang>BNI cabang Cepu antre dan buang-buang waktu</service-kantor cabang> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
cukup capek di bni syariah enggak ada orang dalam , antre kop lama asli | <service-general>cukup capek antre lama asli</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:
|
Gampang banget ya #BukaRekeningBNI #BNIMobileBanking enggak perlu antre lama di bank | <product-simpanan>Gampang banget BukaRekeningBNI enggak perlu antre lama</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:
|
Bni , mandiri selalu antre dan atm - nya sering eror :( | <service-general>selalu antre</service-general>
<facility-atm>atm sering eror</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:
|
Yala .masa antre @BNI 2 jam - an nih . | <service-general>antre 2 jam - an</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:
|
Sudah antre lama banget , pas sudah dipanggil eh ternyata eror . | <service-general>antre lama banget eror</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:
|
Antre ke bni lama benar buset deh | <service-general>Antre lama benar buset</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:
|
Antre @BNI Lama banget , cuman mau ganti atm. Nomor nya enggak antre banyak tetapi lama | <service-general>Antre Lama banget</service-general>
<service-cs>ganti atm enggak antre banyak tetapi lama</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Jadi gue habis transfer .BNI lambat banget anjing kesal , BCA antre , BRI pusat antre . | <service-teller>transfer lambat banget anjing kesal</service-teller>
<service-general>antre 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:
|
Aku BNI saja deh , mandiri antre huh | <service-general>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:
|
@BNICustomerCare @BNI itu call center benaran ada apa asal-asalan .di call center antre sampai 1 jam enggak ada yang angkat .di surel pun respon nya templat | <service-customer center>BNICustomerCare call center enggak ada yang angkat surel respon nya templat</service-customer center> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Antre lebih dari 2 jam hanya untuk buka rekening baru @BNI setelah itu pun proses pembuatan masih bertele-tele lagi . | <service-cs>Antre lebih dari 2 jam buka rekening pembuatan bertele-tele</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 cabang Banjarbaru antre CS lama sekali minimal 1 jam nasabah harus menunggu . | <service-cs>antre CS lama sekali</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Yang aku suka dari bank @BNI ya ini di tempat ku enggak perlu antre lama mbak CS - nya cantik lagi hahah | <service-cs>enggak perlu antre lama CS cantik</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 antre di cs sudah hampir sejam tidak dilayani | <service-cs>antre cs hampir sejam tidak dilayani</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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_corpu BNI KCU Tegal konter cs ada 5 tetapi yang buka cuma 2 .antre banyak banget ini .lama . | <service-cs>konter cs ada 5 buka cuma 2 antre banyak banget ini . lama</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 kok Pelayanan nya Lambat banget .Padahal banyak yang antre . | <service-general>Pelayanan Lambat banget banyak 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:
|
enggak ada yang lebih lama selain antre di BNI cabang godean | <service-general>lama 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:
|
CSO @BNI cabang Tj Karang Unila , sudah cuma 2 , yang antre banyak , internet nya lelet .sesak menunggu nya | <service-cs>CSO cuma 2 antre banyak</service-cs>
<facility-general>internet lelet</facility-general> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@BNI untuk BNI cabang pasar Anyer .Tolong istirahat jangan lama-lama ya .Banyak nasabah antre nih .Cs kemana nih | <service-general>istirahat jangan lama-lama</service-general>
<service-cs>Banyak antre Cs kemana nih</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence 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 perlu antre di bank lagi deh untuk bayar tagihan CC .Bayar via ATM @BNI saja .Ada fitur untuk bayar tagihan CC lo !Suka ! | <facility-atm>enggak perlu antre di bank bayar tagihan CC ATM Ada fitur untuk bayar tagihan CC Suka</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:
|
sudah antre eh diminta surat kehilangan dari kepolisian .Ini info cabang sama call centre enggak sinkron | <service-general>info cabang sama call centre enggak sinkron</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:
|
Untung nya ada ATM BNI , transaksi cepat dan tidak antre !Terima kasih | <facility-atm>Untung ATM transaksi cepat dan tidak antre</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:
|
Setiap ke bank @BNI TULUNGAGUNG selalu antre dan lama bahkan kadang CS - nya enggak penuh | <service-cs>antre lama CS enggak penuh</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Antre CS di bni enggak pernah sebentar .hm | <service-cs>Antre CS enggak pernah sebentar</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Sejam lebih antre di BNI masih belum terlayani , uhg .tidak produktif . | <service-general>Sejam lebih antre tidak produktif</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:
|
@BNI @BNICustomerCare admin pelayanan teller di KCP Cikupa Tangerang Lambat sekali .sudah antre lebih dari 1 jam belum dapat giliran . | <service-teller>pelayanan teller Lambat sekali antre lebih dari 1 jam belum dapat giliran</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:
|
Tolong dong ini CS - nya BNI Syariah tambahkan .Masa iya cuma 2 tetapi yang antre puluhan . | <service-cs>CS cuma 2 antre puluhan</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Baru sekarang lo gue merasakan antre di bank terus pegawai nya bilang " kalau yang buru-buru bisa pindah ke tempat lain " , cuma di @BNI jatimulya | <service-general>pegawai</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:
|
Antre buka ATM BNI panjang banget jhon .lama | <service-cs>Antre buka ATM panjang banget lama</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
karena BNI cepat dalam bertransaksi , tak perlu antre lama-lama : D #BNITaplus | <service-general>cepat bertransaksi tak perlu antre lama-lama</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:
|
@BNI saya sudah antre lama , tiba-tiba datang orang mau bayar pajak enggak mau antre , menyelonong bilang ke satpam & langsung ditangani sama teller , saya kecewa | <service-teller>antre lama teller kecewa</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:
|
Kenapa setiap ke CS BNI pelayanan nya lama ?Antre 3 orang saja sejam lebih , SOP - nya begitu atau bagaimana nih ? | <service-cs>CS pelayanan lama Antre 3 orang saja sejam lebih</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Hari ini kecewa dengan pelayanan CS @BNI cabang the east , gue antre , tetapi pas ada ibu-ibu datang sesudah gue , eh dia yang diterima CS | <service-cs>kecewa pelayanan CS</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
aku lebih suka pakai Mandiri Mobile kak mungkin bisa coba Mandiri Mobile karena lebih mudah | <facility-aplikasi>lebih Mobile lebih mudah</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
penggunaan layanan internet banking Bank BRI lebih mudah dan stabil untuk digunakan daripada Bank Mandiri ya . | <facility-aplikasi>internet banking lebih mudah dan stabil</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Sejauh ini nyaman banget pakai e-money Mandiri versi Indomaret . | <product-e-money>nyaman banget e-money</product-e-money> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Dengan internet banking MANDIRI , semua transaksi menjadi lebih mudah dan nyaman @mandirifiesta | <facility-aplikasi>internet banking transaksi lebih mudah dan nyaman</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
pakai internet banking mandiri itu mudah dan cepat #MandiriArt | <facility-aplikasi>internet banking mudah dan cepat</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bank Mandiri itu membuat transaksi menjadi lebih mudah , apalagi dengan menggunakan internet banking - nya | <facility-aplikasi>transaksi lebih mudah internet banking</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@bankmandiri Transaksi dengan Internet banking Mandiri .Semua jadi mudah , di mana pun bisa ! | <facility-aplikasi>Transaksi Internet banking mudah , di mana pun bisa</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Dengan internet banking / mobile mandiri hidup jadi lebih mudah | <facility-aplikasi>internet banking / mobile lebih mudah</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@mandiricare baik , akan saya sampaikan ke teman-teman .Soal nya internet banking mandiri relatif mudah cara pakai nya dibandingkan dengan lainnya | <facility-aplikasi>internet banking relatif mudah cara pakai</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
mengisi pulsa mudah kapan saja di mana saja dengan mandiri Internet banking | <facility-aplikasi>mengisi pulsa mudah Internet banking</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
@mandirifiesta sejak mengaktifkan sms / mobile / internet banking mandiri , isi pulsa jadi mudah banget | <facility-e-channel>sms / mobile / internet banking isi pulsa mudah 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:
|
@luviku pakai mobile banking atau internet banking mudah cepat Dan aman | <facility-aplikasi>mobile banking atau internet banking mudah cepat Dan aman</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Bayar kuliah mudah pakai mandiri internet banking : D | <facility-aplikasi>Bayar kuliah mudah internet banking</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Sejauh ini benar-benar nyaman , mudah dan PUAS pakai internet banking bank Permata ketimbang Mandiri & BCA !juara Permata ! | <facility-aplikasi>nyaman , mudah dan PUAS pakai internet banking</facility-aplikasi>
<facility-klikbca>nyaman , mudah dan PUAS pakai internet banking</facility-klikbca>
<general>juara</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:
|
@mandirifiesta membuat saya lebih mudah bertransaksi di kantor tanpa harus ke ATM .terima kasih mandiri internet banking | <facility-aplikasi>lebih mudah bertransaksi tanpa harus ke ATM internet banking</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
dengan internet banking mandiri , transaksi jadi mudah .:) | <facility-aplikasi>internet banking transaksi mudah</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Token Mandiri sudah OK :) Internet Banking menjadi lebih Mudah ya :) | <facility-aplikasi>Token sudah OK Internet Banking lebih Mudah</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
Akhirnya punya juga internet banking mandiri .transaksi jadi lebih mudah . | <facility-aplikasi>internet banking transaksi lebih mudah</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
mandiri internet banking lebih mudah daripada mega internet banking | <facility-aplikasi>internet banking lebih mudah internet banking</facility-aplikasi> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|
komplain tentang biaya over limit , tetapi dicatat nya beda !baru ini ada CS BCA bodoh banget ! | <product-kartu kredit>biaya over limit dicatat nya beda</product-kartu kredit>
<service-cs>CS bodoh banget</service-cs> | Task: Extract aspects and corresponding text from the input sentence. Use the provided list of aspects to categorize the extracted text.
Input format: A sentence or short paragraph in Indonesian.
Output format: XML-style tags containing the aspect and corresponding text.
Aspect list:
facility-BCA Mobile
facility-EDC
facility-NFC
facility-aplikasi
facility-atm
facility-deposit box
facility-e-channel
facility-general
facility-kantor
facility-keybca
facility-klikbca
facility-klikpay
facility-m-bca
facility-mesin cs digital
facility-payroll
facility-phone banking
general
general-iklan
general-promo
product-KKB
product-KMK
product-KPR
product-KUR
product-asuransi
product-deposito
product-e-money
product-flazz
product-general
product-giro
product-kartu debit
product-kartu kredit
product-kartu-kredit
product-pinjaman
product-sakuku
product-simpanan
service-cs
service-customer center
service-general
service-haloBCA
service-kantor cabang
service-karyawan
service-prioritas
service-satpam
service-telemarketing
service-teller
service-tukang parkir
Rules for extraction:
1. Identify the most relevant aspect(s) from the list for the given input.
2. Extract the minimal span of text that accurately represents the aspect.
3. If multiple aspects are present, extract each one separately.
4. If no relevant aspect is found, output "NONE"
Examples:
Input: BNI enggak menyediakan jalur teller khusus kliring giro / cek. Padahal kliring giro / cek ada batas waktu nya. Payah!
Output: <service-teller>enggak menyediakan jalur teller khusus kliring giro / cek</service-teller> <general>Payah</general>
Input: Teller Mandiri yang baru ini ribet sekali.
Output: <service-teller>Teller ribet sekali</service-teller>
Input: mau verifikasi kartu kredit saja susah ya, danamon danamon. sudah bagus dipakai lo ini dipersulit. mau nya apa T.T
Output: <product-kartu kredit>verifikasi kartu kredit susah</product-kartu kredit>
Input: Saya sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari.
Output: <facility-BCA Mobile>sangat puas dengan layanan BCA Mobile, sangat memudahkan transaksi sehari-hari</facility-BCA Mobile>
Input: Bank ini tidak memiliki fasilitas apa-apa yang berguna.
Output: <general>tidak memiliki fasilitas apa-apa yang berguna</general>
Input: Siang ini , baik mobile BCA enggak bisa digunakan @HaloBCA internet banking juga lelet .
Output: <facility-BCA Mobile>mobile BCA enggak bisa digunakan</facility-BCA Mobile> <facility-klikbca>internet banking lelet</facility-klikbca>
Input: Iya sih , aplikasi mobile - nya Mandiri lebih bagus dari BCA .
Output: <facility-aplikasi>aplikasi mobile lebih bagus dari</facility-aplikasi> <facility-BCA Mobile>lebih bagus</facility-BCA Mobile>
Input: Cuaca hari ini cerah sekali.
Output: NONE
Handling ambiguity:
- If a sentence could belong to multiple aspects, write all of them
Now, given the input text below, extract the relevant aspects and text:
Input: [text]
Output:
|