Unnamed: 0 int64 0 335k | question stringlengths 17 26.8k | answer stringlengths 1 7.13k | user_parent stringclasses 29
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4,500 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'GIHATAGAN', 'OG', 'AWARD', 'ISIP', ''MOST', 'IMPROVED', ''', 'COMPONENT', 'CITY', 'SA', 'PILIPINAS', 'Giila', 'ang', 'Dumaguete', 'City', 'isip', ''Most', 'Improved', ''', ... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 7, 8, 8, 8, 8, 0, 5, 6, 6, 6, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 1, 2, 0, 0, 1, 2, 0, 3, 4, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 7, 8, 8, 8, 8, 0, 7, 8, 8, 8, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,501 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BRGY.', 'KAGAWAD', 'GIPUSIL', 'PATAY', 'SA', 'BAYAWAN', 'CITY', 'Patay', 'ang', 'usa', 'ka', 'Barangay', 'Kagawad', 'human', 'siya', 'gipusil', 'sa', 'wala', 'pa', 'mailhi', 'nga', 'sus... | [0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,502 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'MAG-UUMA', 'SA', 'DUMAGUETE', 'NAKADAWAT', 'OG', 'BAG-ONG', 'KAGAMITAN', 'ARON', 'MAPAUSBAW', 'ANG', 'PRODUKSYON', 'SA', 'BUGAS', 'Nakadawat', 'ang', 'mga', 'mag-uuma', 'sa', 'da... | [0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 1, 2, 2, 0, 0, 0, 1, 2, 2, 2, 0, 0, 3, 4, 4, 0, 0, 7... | cebuaner |
4,503 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['74.2', 'MILYON', 'KA', 'MGA', 'PINOY', 'ANG', 'NAKAREHISTRO', 'SA', 'NATIONAL', 'ID', ';', '22', 'MILYON', 'ANG', 'NAHIMO', ',', '17.6', 'MILYON', 'ANG', 'NAHATOD', 'Anaa', 'na', 'sa', ... | [0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,504 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LA', 'UNION', 'GOV'T', 'TUGUTAN', 'ANG', 'MGA', 'BABAYING', 'EMPLEYADO', 'NGA', 'MO-WFH', 'ATOL', 'SA', 'ILANG', '"', 'PERIOD', 'DAYS', '"', 'Tugutan', 'ang', 'mga', 'babayi', 'nga', 'n... | [5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,505 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gidayeg', 'sa', 'mga', 'netizens', 'ang', 'artist', 'nga', 'si', 'Nestor', 'Abayon', 'Jr.', 'sa', 'Rizal', 'Occidental', 'Mindoro', 'tungod', 'sa', 'iyang', 'painting', 'nga', 'usa', 'h... | [0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,506 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gideklarar', 'na', 'sa', 'PAGASA', 'ang', 'pagsugod', 'sa', 'northeast', 'monsoon', 'o', 'amihan', 'season', 'niadtong', 'Huwebes', ',', 'Oktubre', '20', ',', '2022', '.'] Use the follo... | [0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,507 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DISNEY+', ',', 'AVAILABLE', 'NA', 'SA', 'PILIPINAS', 'SUGOD', 'KARONG', 'NOBYEMBRE', '17', ',', '2022', 'Ma-access', 'na', 'sa', 'Pilipinas', 'ang', 'streaming', 'service', 'nga', 'Disn... | [7, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 7, 0, 7, 0, 7, 0, 7, 8, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,508 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipagawas', 'na', 'sa', 'lokal', 'nga', 'kagamhanan', 'sa', 'Negros', 'Oriental', 'ang', 'official', 'video', 'alang', 'sa', 'Buglasan', '2022', 'nga', 'gilaumang', 'magsugod', 'karong'... | [0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0] | cebuaner |
4,509 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mosunod', 'mao', 'ang', 'schedule', 'sa', 'mga', 'kalihokan', 'sa', 'Buglasan', 'Festival', 'karon', 'Oktuber', '17-30', ',', '2022', '.'] Use the following schema: 1 = B-WIS: Be... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0] | cebuaner |
4,510 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAPITAN', 'SA', 'PIAPI', ',', 'NIRESIGN', 'ARON', 'MAKAGAHIN', 'OG', 'PANAHON', 'ALANG', 'SA', 'PAMILYA', 'Ni-resign', 'si', 'Mr.', 'Clark', 'L.', 'Labi', 'isip', 'Punong', 'Barangay', ... | [0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,511 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['1,000', 'KA', 'RESIDENTE', 'SA', 'HIMAMAYLAN', ',', 'WALA', 'GIHAPON', 'KAULI', 'TUNGOD', 'SA', 'ENGKWENTRO', 'SA', 'MILITAR', 'UG', 'NPA', 'DIDTO', 'Ubos', 'nalang', 'sa', '1,000', 'ka... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,512 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BES', ',', 'EXCITED', 'NA', 'PUD', 'BA', 'KA', 'SA', 'BUGLASAN', '?', 'Nagsugod', 'na', 'sa', 'pagtukod', 'ang', 'mga', 'Local', 'Government', 'Units', '(', 'LGU', ')', 'sa', 'ilang', '... | [0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,513 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ni-pose', 'alang', 'sa', 'ilang', 'unang', 'litrato', 'ang', 'asawa', 'ni', 'Justin', 'Bieber', 'nga', 'si', 'Hailey', 'Bieber', 'ug', 'ex', 'nga', 'si', 'Selena', 'Gomez', 'atol', 'sa'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 4, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,514 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Video', 'sa', 'pagluwas', 'sa', 'PNP', 'Claveria', 'sa', 'usa', 'ka', 'residente', 'nga', 'na-trap', 'sa', 'sulod', 'sa', 'iyang', 'panimalay', 'sa', 'Barangay', 'Dibalio', ',', 'Claver... | [0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,515 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['1,747', 'DENGUE', 'CASES', 'NATALA', 'SA', 'NEGOR', ';', '8', 'NGA', 'NAMATAY', 'Nakatala', 'og', 'kinatibuk-ang', '1,747', 'ka', 'mga', 'kaso', 'sa', 'dengue', 'ang', 'probinsya', 'sa'... | [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,516 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['COA', 'REPORT', ':', '90', '%', 'SA', 'MGA', 'PAMILYA', 'SA', '4Ps', ',', 'UBOS', 'GIHAPON', 'SA', 'POVERTY', 'THRESHOLD', 'Human', 'sa', '13', 'ka', 'tuig', 'nga', 'pagdawat', 'og', 'c... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,517 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gi-share', 'sa', 'NASA', 'ang', 'hulagway', 'sa', 'duha', 'ka', ''interacting', 'galaxies', ''', 'nga', 'morag', 'nagtapad', 'nga', 'naglutaw', ',', 'kuha', 'sa', 'Hubble', ''s', 'Advan... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 7, 8, 0] | cebuaner |
4,518 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gilaoman', 'nga', 'aduna'y', 'laing', 'pagsaka', 'sa', 'presyo', 'sa', 'gasolina', 'sa', 'mosunod', 'nga', 'semana.', 'Sumala', 'pa', 'sa', 'usa', 'ka', 'oil', 'industry', 'source', ','... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,519 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'GIKONSIDERAR', 'ANG', 'PAGPATUMAN', 'SA', 'PALENG-QR', 'ALANG', 'SA', 'CASHLESS', 'PAYMENTS', 'SA', 'PUBLIC', 'MARKET', ',', 'TRANSPORT', 'HUBS', 'Nakadawat', 'si', 'Mayor'... | [5, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0... | cebuaner |
4,520 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NGCP', 'NAKOMPLETO', 'NA', 'ANG', 'RESTORATION', 'SA', 'AMLAN-SAMBOAN', 'SUBMARINECABLE', 'Malampuson', 'nga', 'gipakusog', 'sa', 'NGCP', 'ang', 'Amlan-Samboan', '138kV', 'Transmission'... | [3, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 3, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,521 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mga', 'hulagway', 'sa', 'blessing', 'sa', 'nagkalain-laing', 'opisina', 'sa', 'Provincial', 'Capitol', 'karong', 'Huwebes', ',', 'Oktubre', '13', ',', '2022', '.'] Use the following sch... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,522 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nakuhaan', 'og', 'video', 'sa', 'netizen', 'nga', 'si', 'Mark', 'Niño', 'Rosellosa', 'ang', 'usa', 'ka', 'King', 'Cobra', 'nga', 'iyang', 'nakit-an', 'sa', 'luyo', 'sa', 'ilang', 'panim... | [0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0] | cebuaner |
4,523 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SEN.', 'TULFO', 'GISUGYOT', 'ANG', 'FULL', 'SCHOLARSHIP', 'ALANG', 'SA', 'NURSING', 'STUDENTS', 'Gisugyot', 'ni', 'Senador', 'Raffy', 'Tulfo', 'niadtong', 'Martes', 'ang', 'probisyon', ... | [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,524 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAPIN', '16,000', 'KA', 'MGA', 'RESIDENTE', ',', 'NIBAKWIT', 'TUNGOD', 'SA', 'PINAKABAG-O', 'NGA', 'ENGWENTRO', 'SA', 'HIMAMAYLAN', 'Nisaka', 'ang', 'numero', 'sa', 'mga', 'nibakwit', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 1, 2, 2, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,525 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Pipila', 'ka', 'mga', 'tigbaligya', 'sa', 'Mandaue', 'City', 'Public', 'Market', 'ang', 'nagdawat', 'na', 'og', 'bayad', 'pinaagi', 'sa', 'GCash.', 'Sumala', 'pa', 'ni', 'Mandaue', 'Cit... | [0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 5, 6, 0, 1, 2, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,526 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GIINGONG', 'LIDER', 'SA', 'NPA', 'SA', 'NEGROS', ',', 'NAPATAY', 'SA', 'ENGKWENTRO', 'Napatay', 'ang', 'usa', 'ka', 'giingong', 'taas', 'nga', 'lider', 'sa', 'NPA', 'sa', 'engkwentro', ... | [0, 0, 0, 3, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,527 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PRES.', 'MARCOS', 'GIPIRMAHAN', 'ANG', 'SIM', 'REGISTRATION', 'LAW', 'TALIWALA', 'SA', 'PAGDAGHAN', 'SA', 'TEXT', 'SCAMS', 'Giaprobahan', 'na', 'ni', 'Presidente', 'Ferdinand', 'Marcos'... | [0, 1, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,528 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DGTE', 'NAGTUKOD', 'OG', 'CENTER', 'ALANG', 'SA', 'MGA', 'MAG-UUMA', 'ARON', 'PAGKAT-ON', 'SA', 'BAG-ONG', 'MGA', 'TEKNOLOHIYA', 'UG', 'MAPALAMBO', 'ANG', 'PRODUKSYON', 'Ma-access', 'na... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0, 5, 0, 0, 0, 1, 2, 2, 0, 3, 4, 4, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,529 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['2', 'KALABAW', ',', 'NAANOD', 'SA', 'BAHA', 'SA', 'MINGLANILLA', 'Tungod', 'sa', 'kusog', 'nga', 'pag-ulan', ',', 'duha', 'ka', 'kalabaw', '(', 'water', 'buffaloes', ')', 'ang', 'nadala... | [0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,530 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['2', 'SUNDALO', 'PATAY', ',', '6', 'SAMARAN', 'SA', 'ENGKWENTRO', 'TALI', 'SA', 'MGA', 'GIINGONG', 'NPA', 'SA', 'NEGROS', 'OCCIDENTAL', 'Duha', 'ka', 'sundalo', 'ang', 'patay', 'samtang'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,531 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['CEBU', 'PACIFIC', 'NAGTANYAG', 'OG', 'P2,499', 'NGA', 'PLETE', 'SA', 'JAPAN', 'Nagtanyag', 'ang', 'Cebu', 'Pacific', 'og', 'promotional', 'seats', 'nga', 'ingon', 'kaubos', 'sa', 'P2,49... | [3, 4, 0, 0, 0, 0, 0, 0, 5, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 5, 0, 5, 0, 0, 0... | cebuaner |
4,532 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['THAILAND', ',', 'NAGBANGOTAN', 'SA', 'MGA', 'BIKTIMA', 'SA', 'MASS', 'KILLING', 'LOOK', ':', '34', 'ka', 'mga', 'tawo', 'ang', 'namatay', 'sa', 'Thailand', 'niadtong', 'Huwebes', ',', '... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,533 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gibalik', 'pag-usab', 'sa', 'Jollibee', 'ang', 'lamian', 'nga', 'Garlic', 'Pepper', 'Beef', 'sa', 'P95', '!', 'Anaa', 'lamang', 'kini', 'sa', 'Mega', 'Manila', 'Stores', 'pinaagi', 'sa'... | [0, 0, 0, 5, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,534 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JAPANESE', 'CONSUL', 'GENERAL', ',', 'MAYOR', 'REMOLLO', 'NISAAD', 'SA', 'PAGPALAMBO', 'SA', 'PANAGHIGALAAY', 'Nibisita', 'si', 'Consul', 'General', 'sa', 'Japan', 'sa', 'Cebu', 'Hideki... | [7, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 1, 2, 0, 0, 5, 6, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 7... | cebuaner |
4,535 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mga', 'supporter', 'ni', 'Pryde', 'Henry', 'Teves', 'nagtigom', 'sa', 'gawas', 'sa', 'Kapitolyo', 'karong', 'hapon.', 'Gilaoman', 'ang', 'posibleng', 'pagtake-over', 'ni', 'Gov.', 'Roel... | [0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0] | cebuaner |
4,536 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BUGNAW', 'NGA', 'PANAHON', ',', 'GILAOMAN', 'SA', 'MGA', 'MOSUNOD', 'NGA', 'ADLAW', 'Gilaoman', 'karon', 'sa', 'Pilipinas', 'ang', 'anam-anam', 'nga', 'pag-abot', 'sa', 'northeast', 'mo... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,537 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAYOR', 'NA', ',', 'DRIVER', 'PA', 'Si', 'Bais', 'City', 'Mayor', 'Luigi', 'Marcel', 'Teves', 'Goñi', 'mao'y', 'nangunay', 'sa', 'pagmaneho', 'sa', 'chariot', 'nga', 'mao'y', 'gihimong'... | [0, 0, 0, 0, 0, 0, 5, 6, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,538 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mobalik', 'pag-usab', 'sa', 'Manila', 'si', 'American', 'R', '&', 'B', 'singer', 'ug', 'three-time', 'Grammy', 'winner', 'Ne-Yo', 'alang', 'sa', 'usa', 'ka', 'concert', 'karong', 'Enero... | [0, 0, 0, 5, 0, 7, 8, 8, 8, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0] | cebuaner |
4,539 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['TEACHER', 'SA', 'CEBU', ',', 'NAMATAY', 'SA', 'AKSIDENTE', 'ATOL', 'SA', 'MISMONG', 'ADLAW', 'SA', 'MGA', 'MAGTUTUDLO', 'Patay', 'ang', 'usa', 'ka', 'magtutudlo', 'sa', 'Minglanilla', '... | [0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 5, 6, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,540 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['INFLATION', 'RATE', 'SA', 'PILIPINAS', 'NISAKA', 'SA', '6.9', '%', 'SA', 'SETYEMBRE', 'GIKAN', '6.3', '%', 'SA', 'AGOSTO', 'Nisaka', 'ngadto', 'sa', '6.9', '%', 'ang', 'inflation', 'rat... | [0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4... | cebuaner |
4,541 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Karong', 'adlawa', ',', 'Oktubre', '5', ',', '2022', ',', 'atong', 'isaulog', 'ang', '#', 'WorldTeachersDay2022.', 'Usa', 'ka', 'dako', 'nga', 'pagsaludo', 'sa', 'tanan', 'nga', 'mga', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,542 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['19', 'OUTSTANDING', 'JOB', 'ORDER', 'PERSONNEL', ',', 'GIHATAGAN', 'OG', 'PASIDUNGOG', 'SA', 'KAGAMHANAN', 'SA', 'DUMAGUETE', '19', 'ka', 'mga', 'job', 'order', 'personnel', 'gikan', 's... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 5, 6, 6, 0, 0, 0... | cebuaner |
4,543 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PAGSEMENTO', 'SA', 'DALAN', 'NGA', 'APIL', 'SA', 'METRO', 'DUMAGUETE', 'DIVERSION', 'ROAD', ',', 'NAGPADAYON', 'Nagpadayon', 'ang', 'pagtrabaho', 'sa', 'dalan', 'nga', 'apil', 'sa', 'gi... | [0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,544 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'MAGTUTUDLO', 'SA', 'BAIS', 'CITY', ',', 'NAKADAWAT', 'OG', 'REGALO', 'ALANG', 'SA', 'SELEBRASYON', 'SA', 'WORLD', 'TEACHERS', 'DAY', 'Nakadawat', 'ang', 'mga', 'magtutudlo', 'sa'... | [0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,545 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Lima', 'ka', 'taga-Negros', 'Oriental', 'ang', 'suwerteng', 'nalakip', 'sa', '433', 'ka', 'mananaug', 'sa', 'sa', 'P236-million', 'jackpot', 'prize', '6', '/', '55', 'Grand', 'Lotto', '... | [0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,546 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'talagsaong', 'higayon', ',', '433', 'ka', 'tawo', 'ang', 'nidaug', 'sa', 'P236-million', 'nga', 'jackpot', 'sa', '6', '/', '55', 'Grand', 'Lotto', 'karong', 'gabii', ',', 'sumala'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,547 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GINIKANAN', 'SA', 'CHILD', 'LABORERS', 'NAKABATON', 'OG', 'SKILLS', 'SA', 'PAGLUTO', 'ALANG', 'SA', 'ILANG', 'PANGINABUHI', 'Nagpahigayon', 'og', 'skills', 'training', 'ang', 'dakbayan'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 1, 2, 2, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,548 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MOTOR', 'NIDAM-AG', 'SA', 'NAKA-STANDBY', 'NGA', 'TRUCK', 'SA', 'ZAMBOANGUITA', ';', 'DRIVER', 'SA', 'MOTOR', 'PATAY', 'Usa', 'ang', 'patay', 'human', 'maaksidente', 'ang', 'iyang', 'gi... | [0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,549 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dili', 'magpapildi', 'ang', 'mga', 'estudyante', 'sa', 'Grade', '10', '-', 'Saturn', ',', 'Cluster', 'A', 'sa', 'Piapi', 'High', 'School', 'sa', ''No', 'Bag', 'Challenge.', ''', 'Ang', ... | [0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,550 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipagawas', 'sa', 'James', 'Webb', 'ug', 'Hubble', 'telescopes', 'ang', 'mga', 'unang', 'hulagway', 'sa', 'pagbangga', 'sa', 'DART', 'spaceship', 'sa', 'asteroid', 'nga', 'Dimorphos', '... | [0, 0, 1, 2, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 7, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,551 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['COMELEC', ',', 'GIMANDO', 'NA', 'ANG', 'PAG-ANNUL', 'SA', 'KADAUGAN', 'NI', 'GOV.', 'TEVES', 'NIADTONG', 'MAYO', 'Gimando', 'na', 'sa', 'Commission', 'on', 'Elections', '(', 'Comelec', ... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 1, 2... | cebuaner |
4,552 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DOH', ':', 'PILIPINAS', ',', 'KULANG', 'OG', '106,000', 'KA', 'NURSES', 'Gibutyag', 'sa', 'Department', 'of', 'Health', '(', 'DOH', ')', 'niadtong', 'Huwebes', 'nga', 'kulang', 'ang', '... | [3, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,553 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KRIMEN', 'SA', 'DUMAGUETE', ',', 'MIUS-OS', 'NGADTO', 'SA', '25.27', '%', 'KARONG', 'TUIGA', 'Mius-os', 'ang', 'mga', 'insidente', 'sa', 'krimen', 'sa', 'dakbayan', 'sa', 'Dumaguete', '... | [0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 1, 2, 2, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,554 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BRIDE', 'NGA', 'WALA', 'GITUNGHA', 'SA', 'IYANG', 'GROOM', ',', 'GIPADAYON', 'ANG', 'SEREMONYA', ',', 'PARTY', 'UBAN', 'SA', 'IYANG', 'PAMILYA', ',', 'HIGALA', 'Usa', 'ka', 'bride', 'an... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,555 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gidayeg', 'sa', 'Taste', 'Atlas', ',', 'usa', 'ka', 'food', 'website', ',', 'ang', 'Lumpiang', 'Shanghai', 'isip', 'ikaduha', 'sa', 'best', 'street', 'food', 'sa', 'kalibutan', '.'] Use... | [0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,556 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagdala', 'og', 'dakong', 'kadaot', 'sa', '#', 'CentralVietnam', 'ang', 'Typhoon', '#', 'Noru', 'human', 'kini', 'mag-landfall', 'sa', 'ilang', 'nasud', 'ganihang', 'buntag.', 'Ang', 'T... | [0, 0, 0, 0, 0, 0, 5, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
4,557 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SILLIMAN', 'UNIVERSITY', 'GIILA', 'PAG-USAB', 'ISIP', 'USA', 'KA', 'NATIONAL', 'HISTORICAL', 'LANDMARK', 'Ginganlan', 'pag-usab', 'ang', 'Silliman', 'University', 'isip', 'usa', 'ka', '... | [3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 1, 2, 2, 0, 3, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 3, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3... | cebuaner |
4,558 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nibalik', 'na', 'gyud', 'human', 'ang', 'duha', 'ka', 'tuig', 'ang', 'inila', 'nga', 'Jan-Jan', 'Carnival', 'sa', 'Valencia', ',', 'isip', 'pagsaulog', 'sa', 'tinuig', 'nga', 'pista', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0] | cebuaner |
4,559 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BABAYI', 'NGA', 'NAANOD', 'SA', 'SUBA', 'SA', 'TAYASAN', ',', 'NAKIT-AN', 'NA', 'Nakit-an', 'na', 'ang', 'patay'ng', 'lawas', 'sa', 'usa', 'ka', 'babayi', 'nga', 'naanod', 'sa', 'baha',... | [0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,560 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DAKONG', 'ISDA', ',', 'NAPANA', 'SA', 'RIZAL', 'BOULEVARD', 'Nahimong', 'masuwertehon', 'ang', 'Lunes', 'sa', 'usa', 'ka', 'mamanaay', '(', 'spear', 'fisher', ')', 'human', 'kini', 'nak... | [0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,561 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagpahigayon', 'og', 'aerial', 'inspection', 'si', 'Presidente', 'Ferdinand', 'Marcos', 'Jr.', 'sa', 'mga', 'apektado', 'nga', 'lugar', 'sa', 'Bagyong', '#', 'KardingPH', 'sama', 'sa', ... | [0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 5, 0, 5, 6, 0, 0, 5, 0] | cebuaner |
4,562 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Aduna'y', 'kausbanan', 'sa', 'presyo', 'sa', 'gasolina', 'sa', 'Pilipinas', 'SHELL', 'ugmang', 'adlawa', ',', 'Setyembre', '27', ',', '2022', '.'] Use the following schema: 1 = B-WIS: B... | [0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,563 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Pinakagrabe', 'nga', 'naigo', 'sa', 'Bagyong', '#', 'KardingPH', 'ang', 'Bongliw', ',', 'usa', 'ka', 'komunidad', 'sa', 'Barangay', 'Rizal', ',', 'Panukulan', ',', 'Polillo', 'Island.',... | [0, 0, 0, 0, 7, 8, 8, 0, 5, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 1, 2, 0, 0, 1, 2, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,564 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Naguba', 'ang', 'mga', 'kabalayan', 'ug', 'imprastraktura', 'human', 'niigo', 'ang', 'Bagyong', '#', 'KardingPH', 'sa', 'munisipalidad', 'sa', 'Burdeos', 'sa', 'Polillo', 'Island', ',',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 5, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,565 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Naguba', 'ang', 'mga', 'kabalayan', 'ug', 'sakayan', 'sa', 'Barangay', 'Paltic', ',', 'Dingalan', ',', 'Aurora', 'human', 'sa', 'Bagyong', '#', 'KardingPH', 'nga', 'niigo', 'sa', 'Luzon... | [0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 0, 0, 7, 8, 8, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,566 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Walay', 'klase', 'karong', 'adlawa', '(', 'Sept.', '26', ',', '2022', ')', 'sa', '6', 'ka', 'lugar', 'sa', 'Negros', 'Oriental', 'tungod', 'sa', 'epekto', 'sa', 'Bagyong', '#', 'Karding... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 3, 4, 4, 0] | cebuaner |
4,567 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Walay', 'klase', 'sa', 'tanang', 'pampubliko', 'og', 'pribadong', 'eskuwelahan', 'sa', 'lungsod', 'sa', 'Tayasan', 'karong', 'Lunes', ',', 'Sept.', '26', ',', '2022', ',', 'tungod', 'sa... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0] | cebuaner |
4,568 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['IKOG', 'NI', 'SUPER', 'TYPHOON', 'KARDING', ',', 'NABATI', 'SA', 'SIQUIJOR', 'Bisan', 'pa', 'man', 'og', 'dili', 'direktang', 'maigo', 'ang', 'probinsya', 'sa', 'Siquijor', 'sa', 'Bagyo... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,569 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagpagawas', 'ang', 'PAGASA', 'og', 'rainfall', 'advisory', 'sa', 'Negros', 'Oriental', ',', 'habagatang', 'Sugbo', ',', 'ug', 'Siquijor.', 'Padayong', 'makasinati', 'ang', 'atong', 'pr... | [0, 0, 3, 0, 0, 0, 0, 5, 6, 0, 0, 5, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0] | cebuaner |
4,570 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SIGNAL', 'NO.', '5', ',', 'GIISA', 'NA', 'TUNGOD', 'SA', 'BAGYONG', 'KARDING', 'Gipaubos', 'na', 'ang', 'pipila', 'ka', 'lugar', 'sa', 'Luzon', 'sa', 'Signal', 'No.', '5', 'tungod', 'sa... | [0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0] | cebuaner |
4,571 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KARDING', ',', 'USA', 'NA', 'KA', 'SUPER', 'TYPHOON', 'Mas', 'nikusog', 'pa', 'ug', 'nahimo', 'nang', 'hingpit', 'nga', 'super', 'typhoon', 'ang', 'Bagyong', '#', 'KardingPH.', 'Kini', ... | [7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 7, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,572 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BAKA', 'GUSTO', 'MO-ESKUWELA', '!', 'LOOK', ':', 'Nabulabog', 'ang', 'klase', 'ni', 'Ma'am', 'Neneng', 'Portrias', 'Garaula', 'human', 'aduna'y', 'usa', 'ka', 'puting', 'baka', 'ang', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 5, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,573 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NATIONWIDE', 'BAKUNAHANG', 'BAYAN', ',', 'IPAHIGAYON', 'SUNOD', 'SEMANA', ';', 'MODAWAT', 'OG', 'WALK-INS', 'Maghatag', 'na', 'sab', 'og', 'primary', 'o', 'booster', 'doses', 'sa', 'Cov... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,574 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NAPALGANG', 'PATAYNG', 'LAWAS', 'SA', 'USA', 'KA', 'DALAGA', ',', 'NAILHAN', 'NA', 'Napalgan', 'ang', 'patay'ng', 'lawas', 'sa', 'babayi', 'sa', 'usa', 'ka', 'hotel', 'sa', 'Real', 'St.... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 5, 6, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,575 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PROYEKTO', 'NGA', 'PAGTUKOD', 'OG', 'BOULDER', 'DIKES', ',', 'KANAL', 'SA', 'BANILAD-MANGNAO', ',', 'NAGPADAYON', 'Nagpadayon', 'ang', 'pagtrabaho', 'sa', 'proyekto', 'sa', 'Barangay', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 6, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,576 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NAPALGANG', 'PATAYNG', 'LAWAS', 'SA', 'USA', 'KA', 'DALAGA', ',', 'NAILHAN', 'NA', 'Napalgan', 'ang', 'patay'ng', 'lawas', 'sa', 'babayi', 'sa', 'usa', 'ka', 'hotel', 'sa', 'Real', 'St.... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 5, 6, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,577 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JULIA', 'BARRETTO', 'NAG-RELAX', 'UG', 'NAGPAMASAHE', 'SA', 'PANTAWAN', 'PEOPLE’S', 'PARK', 'Nibisita', 'si', 'Julia', 'Barretto', 'ug', 'iyang', 'grupo', 'sa', 'Pantawan', 'People', ''... | [1, 2, 0, 0, 0, 0, 5, 6, 6, 0, 0, 1, 2, 0, 0, 0, 0, 5, 6, 6, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 2, 2, 0, 3, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 1, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0... | cebuaner |
4,578 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'NAKADAWAT', 'OG', '5-STAR', 'RATING', 'ALANG', 'SA', 'ENERGY', ',', 'FUEL', 'CONSERVATION', 'Nakadawat', 'ang', 'kagamhanan', 'sa', 'dakbayan', 'sa', 'Dumaguete', 'og', 'pu... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 3, 4, 4, 4, 4, 4, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0... | cebuaner |
4,579 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['3', 'KA', 'TAAS', 'NGA', 'OPISYAL', 'SA', 'NPA', 'UG', '13', 'UBAN', 'PA', ',', 'MITAHAN', 'SA', 'MGA', 'AWTORIDAD', 'Misurender', 'ang', '16', 'ka', 'giingong', 'rebelde', 'apil', 'na'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 0, 1, 2, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0... | cebuaner |
4,580 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JULIA', 'BARRETTO', 'NAKIGPULONG', 'SA', 'MGA', 'LOKAL', 'NGA', 'OPISYAL', 'SA', 'DUMAGUETE', 'Nibisita', 'ang', 'aktres', 'ug', 'blogger', 'nga', 'si', 'Julia', 'Barretto', 'ni', 'Mayo... | [1, 2, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 5, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,581 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SUMC', 'FOUNDATION', 'INCORPORATED', ',', 'NIDONAR', 'OG', 'LIBOAN', 'KA', 'MGA', 'PPE', 'SA', 'DUMAGUETE', 'Nagdonar', 'ang', 'Silliman', 'University', 'Foundation', 'Incorporated', 'o... | [3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 1, 2, 2, 0, 3, 0, 0, 0, 0, 0, 0, 3, 4, 0, 3, 0, 0, 0... | cebuaner |
4,582 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PISI', ',', 'CEMAP', 'NAGPAHIGAYON', 'OG', 'INFORMATION', 'AND', 'EDUCATION', 'CAMPAIGN', 'ALANG', 'SA', 'MGA', 'RETAILER', 'SA', 'KABILYA', 'Nagpahigayon', 'og', 'Information', 'and', ... | [3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,583 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DEPED', ':', 'P532-M', 'BUDGET', 'ALANG', 'SA', 'SPED', 'SUNOD', 'TUIG', ',', 'GIBASURA', 'Gibasura', 'ang', 'P532-million', 'nga', 'special', 'education', '(', 'SPED', ')', 'budget', '... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,584 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JUST', 'IN', ':', 'PAG-POSTPONE', 'SA', 'BRGY', ',', 'SK', 'ELECTIONS', ',', 'GIAPROBAHAN', 'NA', 'Giaprobahan', 'sa', 'House', 'of', 'Representatives', 'ang', 'House', 'Bill', '4673', ... | [0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,585 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Aduna'y', 'ipahigayon', 'nga', 'Local', 'Job', 'Fair', 'sa', 'Robinsons', 'Place', 'sa', 'Barangay', 'Calindagan', 'sa', 'dakbayan', 'sa', 'Dumaguete', 'karong', 'Sabado', ',', 'Setyemb... | [0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,586 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['RADIO', 'ANNOUNCER', 'SA', 'MABINAY', ',', 'GIDUNGGAB', 'PATAY', 'Patay', 'ang', 'usa', 'ka', 'radio', 'anchor', 'ug', 'commentator', 'sa', 'lungsod', 'sa', 'Mabinay', 'human', 'siya', ... | [0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6... | cebuaner |
4,587 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'selebrasyon', 'sa', 'Global', 'Handwashing', 'Day', '2022', ',', 'giimbitar', 'sa', 'Metro', 'Dumaguete', 'Water', 'ang', 'mga', 'talentadong', 'dance', 'group', 'sa', 'tibuok', '... | [0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 6, 6, 0] | cebuaner |
4,588 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JAPAN', 'GILAOMANG', 'IBALIK', 'ANG', 'VISA-FREE', 'TOURIST', 'TRAVEL', 'KARONG', 'OKTUBRE', 'Gilaoman', 'nga', 'tangtangon', 'sa', 'Japan', 'ang', 'pag-ban', 'sa', 'indibidwal', 'nga',... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,589 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gibahaan', 'ang', 'Nangka', 'Elementary', 'School', 'sa', 'dakbayan', 'sa', 'Bayawan', 'tungod', 'sa', 'binuntagay', 'nga', 'pag-ulan', 'nga', 'dala', 'sa', 'habagat', 'nga', 'gipakusog... | [0, 0, 3, 4, 4, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,590 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'PATAY', 'HUMAN', 'MALUMOS', 'SA', 'SUBA', 'SA', 'SIBULAN', 'Usa', 'ka', 'lalaki', 'ang', 'patay', 'human', 'nalumos', 'sa', 'suba', 'sa', 'Barangay', 'Ajong', 'sa', 'lungsod',... | [0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0... | cebuaner |
4,591 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'dako', 'punoan', 'sa', 'Acasia', 'ang', 'nibalabag', 'sa', 'dalan', 'human', 'kini', 'matumba', 'tungod', 'sa', 'kusog', 'nga', 'ulan', 'dala', 'sa', 'habagat', 'nga', 'gip... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,592 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['METRO', 'DUMAGUETE', 'WATER', ',', 'NANGHATAG', 'OG', 'CELLPHONES', 'PARA', 'SA', 'PAGLUSAD', 'SA', 'BARANGAY', 'HOTLINES', 'Nanghatag', 'og', 'mga', 'cellphone', 'ang', 'Metro', 'Dumag... | [3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 3, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,593 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['WHO', ':', 'KATAPUSAN', 'SA', 'PANDEMYA', 'SA', 'COVID-19', ',', 'MAKITA', 'NA', 'Wala', 'pa', 'sa', 'posisyon', 'ang', 'kalibutan', 'aron', 'tapuson', 'ang', 'pandemya', 'sa', 'Covid-1... | [3, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,594 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GISUGYOT', 'NGA', 'SIM', 'REGISTRATION', ',', 'GIHISGUTAN', 'PAG-USAB', 'SA', 'SENADO', 'Gidepensahan', 'pag-usab', 'ni', 'Senador', 'Grace', 'Poe', 'ang', 'gisugyot', 'niya', 'nga', 'b... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,595 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['INFLATION', 'RATE', 'SA', 'CENTRAL', 'VISAYAS', ',', 'NISAKA', 'NGADTO', 'SA', '7.4', '%', 'Natala', 'sa', 'Central', 'Visayas', 'ang', 'pinakataas', 'nga', 'inflation', 'rate', 'niadto... | [0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5... | cebuaner |
4,596 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SRA', 'NI-ISYU', 'OG', 'IMPORT', 'ORDER', 'SA', 'HANGTOD', '150,000', 'METRIC', 'TONS', 'SA', 'KALAMAY', 'Gitugotan', 'sa', 'Sugar', 'Board', 'sa', 'Sugar', 'Regulatory', 'Administratio... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0... | cebuaner |
4,597 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DGTE', ',', 'MAGPAHIGAYON', 'OG', 'FAMILY', 'FUN', 'RUN', ',', 'HEALTHY', 'DANCING', 'KARONG', 'SEPT.', '25', 'NGA', 'ADUNAY', 'CASH', 'PRIZES', 'Giimbitar', 'ang', 'tanan', 'nga', 'moa... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 7, 8, 0, 5, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0... | cebuaner |
4,598 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'CITY', 'POLICE', 'STATION', ',', 'RANK', 'NO.', '1', 'SA', 'KAMPANYA', 'BATOK', 'ILEGAL', 'NGA', 'SUGAL', 'Nakadawat', 'ang', 'Dumaguete', 'City', 'Police', 'Station', 'og'... | [3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,599 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['AMERIKA', 'NANGINAHANGLAN', 'OG', 'MGA', 'NURSE', ';', 'P400K', 'ANG', 'SUWELDO', 'Giingnong', 'nagkinahanglan', 'ang', 'Amerika', 'og', 'mga', 'registered', 'nurse', 'nga', 'moabot', '... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 3, 4, 4, 4, 0, 0, 0, 0... | cebuaner |
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