Unnamed: 0 int64 0 335k | question stringlengths 17 26.8k | answer stringlengths 1 7.13k | user_parent stringclasses 29
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4,600 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gitugtan', 'na', 'ang', 'BOLUNTARYONG', 'pagsul-ob', 'og', 'face', 'masks', 'OUTDOORS', 'sa', 'tibuok', 'Pilipinas.', 'Kini', 'human', 'giluwatan', 'ni', 'Presidente', 'Ferdinand', 'Mar... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 3, 4, 0] | cebuaner |
4,601 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['61', 'KA', 'MIGRANTE', 'NGA', 'NATANGGONG', 'SA', 'TUNGA', 'SA', 'DAGAT', 'SA', 'MALTA', ',', 'NALUWAS', 'Naluwas', 'sa', 'BBC', 'Pearl', 'ang', '61', 'ka', 'mga', 'migrante', 'kinsa', ... | [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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 5, 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, 7, 0, 7, 0... | cebuaner |
4,602 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAGTIAYONG', 'NEGOSYANTE', 'NGA', 'CHINESE', 'NATIONAL', 'SA', 'TANJAY', 'CITY', ',', 'GIPUSIL', 'Nakaangkon', 'og', 'samad', 'pinusilan', 'ang', 'mag-asawang', 'negosyante', 'nga', 'Ch... | [0, 0, 0, 7, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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, 0, 1, 2, 0, 0, 0, 0, 0, 1, 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 3, 4, 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... | cebuaner |
4,603 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Alang', 'sa', 'mga', 'estudyante', 'nga', 'nakasinati', 'og', 'krisis', 'ug', 'buot', 'mo-apply', 'sa', 'Educational', 'Assistance', ',', 'palihog', 'i-scan', 'ang', 'BAG-O', 'NGA', 'QR... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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] | cebuaner |
4,604 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BAHO’G', 'ILOK', ',', 'WALA'Y', 'LIGO', 'DILI', 'KA-DRIVE', 'Nagpasa', 'og', 'resolusyon', 'ang', 'Barangay', 'Council', 'sa', 'Pooc', 'sa', 'Talisay', 'City', ',', 'Cebu', 'nga', 'nagd... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,605 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'babaye', 'ang', 'nabiktima', 'sa', 'pagbinastos', 'sa', 'usa', 'ka', 'lalake', 'nga', 'nahitabo', 'usa', 'ka', 'coffee', 'shop', 'sa', 'dakbayan', 'sa', 'Dumaguete', 'mga',... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,606 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETEÑO', 'GIBALIK', 'ANG', 'NAKIT-ANG', '$', '7,345', 'CANADIAN', 'DOLLARS', 'NGADTO', 'SA', 'TAG-IYA', 'Dalaygon', 'ang', 'pagkamatinud-anon', 'ni', 'Junrey', 'E.', 'Cadeliña', ',... | [7, 0, 0, 0, 0, 0, 7, 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, 7, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 5, 6, 6, 6, 6, 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 |
4,607 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Abrihon', 'na'g', 'balik', 'sa', 'Department', 'of', 'Social', 'Welfare', 'and', 'Development', '(', 'DSWD', ')', '-', 'Region', '7', 'ang', 'ONLINE', 'REGISTRATION', 'LINK', 'alang', '... | [0, 0, 0, 0, 3, 4, 4, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 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] | cebuaner |
4,608 | 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', '₱79', 'UG', '₱199', 'FLIGHTS', 'SA', 'ILANG', '9.9', 'SEAT', 'SALE', 'Nagtanyag', 'ang', 'Cebu', 'Pacific', 'og', 'holiday', '"', '9.9', 'seat... | [3, 4, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 5... | cebuaner |
4,609 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gisugdan', 'na', 'sa', 'mobile', 'wallet', 'provider', 'nga', 'GCash', 'ang', 'pagtangtang', 'sa', 'mga', 'letra', 'sa', 'pangalan', 'sa', 'account', 'kung', 'mohimo', 'og', 'mga', 'tra... | [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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,610 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['1', 'KA', 'NPA', 'PATAY', 'SA', 'ENGKWENTRO', 'BATOK', 'SA', 'MILITAR', 'SA', 'GUIHULNGAN', 'CITY', 'Usa', 'ka', 'giingon', 'NPA', 'ang', 'napatay', 'sa', 'engkwento', 'batok', 'sa', 'm... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 3, 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, 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, 3, 4, 4, 4, 4, 4, 4, 4, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 1, 2... | cebuaner |
4,611 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Girekomenda', 'sa', 'Inter-Agency', 'Task', 'Force', 'nga', 'himoong', 'BOLUNTARYO', 'na', 'lamang', 'ang', 'pagsul-ob', 'og', 'face', 'mask', 'sa', 'tibuok', 'nasud.', 'Kini', 'sumala'... | [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, 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, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0] | cebuaner |
4,612 | 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', 'hulagway', 'gikan', 'sa', 'malamposon', 'nga', '2022', 'Titanic', 'expedition', 'sa', 'pagkuha', 'sa', 'world', ''s', 'first', '8K', 'footage', 'sa', 'nalunod', '... | [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, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,613 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BABAYE', 'SA', 'CEBU', ',', 'NADAKPAN', 'HUMAN', 'GIINGONG', 'GIGUBA', 'ANG', 'TV', 'SA', 'VIDEOKEHAN', 'SAMTANG', 'HUBOG', 'Usa', 'ka', 'lalake', 'ug', 'tulo', 'ka', 'babaye', 'ang', '... | [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, 5, 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] | cebuaner |
4,614 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SR.', 'MILA', 'SILAB', ',', 'OPISYAL', 'NANG', 'NILINGKOD', 'ISIP', 'IKA-4', 'NGA', 'PRESIDENTE', 'SA', 'SPUD', 'Opisyal', 'na', 'nga', 'ikaupat', 'nga', 'Univerity', 'President', 'sa',... | [0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 7, 8, 8, 0, 0, 0, 1, 2, 2, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 3, 4, 4, 4, 4, 0... | cebuaner |
4,615 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NORECO', 'II', ',', 'GI-SUSPENSO', 'ANG', 'PAGPANINGIL', 'OG', '10', '%', 'PENALTY', 'SA', 'MGA', 'LATE', 'MAMAYAD', 'OG', 'BILL', 'Hingpit', 'na', 'nga', 'ipatuman', 'sa', 'NORECO', 'I... | [3, 4, 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, 7, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,616 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Niubos', 'na', 'sab', 'ang', 'bili', 'sa', 'atong', 'piso', 'kontra', 'dolyar', 'karong', 'adlawa', ',', 'Sept.', '6', ',', '2022.', 'Nisira', 'ang', 'peso-dollar', 'exchange', 'sa', 'P... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,617 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LA', 'LIBERTAD', ',', 'NAGTANYAG', 'OG', 'MGA', 'BIKE', 'GIKAN', 'SA', 'JAPAN', 'SA', 'PRESYONG', 'P1,000', 'Nagtanyag', 'ang', 'kagamhanang', 'lungsod', 'sa', 'La', 'Libertad', 'og', '... | [5, 6, 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, 5, 0, 0, 0, 0, 0, 0, 5, 6, 0, 1, 2, 2, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,618 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ania', 'ang', 'pamahayag', 'sa', 'NORECO', 'II', 'nunot', 'sa', 'nadawat', 'nila', 'nga', 'order', 'gikan', 'sa', 'Energy', 'Regulatory', 'Commission', '.'] Use the following schema: 1 ... | [0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0] | cebuaner |
4,619 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NTC-7', ',', 'NAGPAHIMANGNO', 'BATOK', 'SA', 'MGA', 'PERSONALIZED', 'TEXT', 'SCAM', 'NGA', 'NAGTANYAG', 'OG', 'TRABAHO', 'UG', 'KWARTA', 'Nagpahimangno', 'ang', 'National', 'Telecommuni... | [3, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,620 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NORECO', 'II', ',', 'GIMANDUAN', 'NGA', 'IPAHUNONG', 'ANG', 'PAGKOLEKTA', 'OG', '10', '%', 'PENALTY', 'SA', 'MGA', 'LATE', 'MAMAYAD', 'OG', 'BILL', 'SA', 'KURYENTE', 'Gimando', 'sa', 'E... | [3, 4, 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, 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, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 3, 4, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 7, 8, 0, 7, 8, 0, 0, 0... | cebuaner |
4,621 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BALAODNON', 'PAG-BAN', 'SA', 'MGA', 'JUNK', 'FOOD', 'SA', 'MGA', 'PAMPUBLIKONG', 'ESKWELAHAN', ',', 'GIDUSO', 'NI', 'SEN.', 'LITO', 'LAPID', 'Gipasaka', 'ni', 'Senador', 'Lito', 'Lapid'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 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, 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, 1, 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... | cebuaner |
4,622 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Special', 'guests', 'of', 'honor', 'sa', 'Maskara', 'Festival', '2022', 'sa', 'Bacolod', 'sila', 'si', 'President', 'Ferdinand', '"', 'Bongbong', '"', 'Marcos', 'Jr.', ',', 'iyang', 'as... | [0, 0, 0, 0, 0, 7, 8, 0, 0, 5, 0, 0, 0, 1, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 2, 0, 7, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 5, 6, 0, 1, 2, 2, 2, 2, 2, 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... | cebuaner |
4,623 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', ',', 'GIDUNGGAB', 'TUNGOD', 'SA', 'AWAY', 'SA', 'MANSANITAS', 'Gidunggab', 'ang', 'usa', 'ka', 'lalaki', 'sa', 'Sibulan', 'niadtong', 'Sabado', 'tungod', 'lamang', 'sa', 'giing... | [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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 5, 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, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,624 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SC', ':', 'ILEGAL', ',', 'DISKRIMINASYON', 'ANG', 'PAGPAPAHAWA', 'SA', 'USA', 'KA', 'EMPLEYADO', 'TUNGOD', 'NAKIGMINYO', 'KINI', 'SA', 'IYANG', 'KATRABAHO', 'Gideklara', 'sa', 'Supreme'... | [3, 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, 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, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1... | cebuaner |
4,625 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DEPED', ':', 'GENDER-RESPONSIVE', 'EDUCATION', 'POLICY', ',', 'IPATUMAN', 'SA', 'TANANG', 'ELEMENTARY', ',', 'HIGH', 'SCHOOL', 'SA', 'TANANG', 'REHIYON', 'Strikto', 'nga', 'ipatuman', '... | [1, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 0, 7, 8, 8, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,626 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'YELLOW', 'FINS', ',', 'NAKADAOG', 'SA', '4', 'KA', 'CATEGORY', 'SA', 'MANDANI', 'BAY', 'DRAGON', 'BOAT', 'REGATTA', '2022', 'Nakadaog', 'ang', 'Dumaguete', 'Yellow', 'Fins'... | [3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 5, 6, 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, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,627 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SUGBO', 'URBAN', 'TRANSIT', 'INC.', ',', 'NAGSUGOD', 'NA', 'SA', 'ILANG', 'CEBU', 'CITY-SIQUIJOR', 'ISLAND', 'TRIP', 'Niabot', 'na', 'ang', 'Sugbo', 'Urban', 'Transit', 'Inc.', '(', 'SU... | [3, 4, 4, 4, 0, 0, 0, 0, 0, 5, 6, 5, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 5, 0, 0, 0, 0, 0, 0, 5, 6, 5, 0, 0, 0, 0, 5, 6, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 5, 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, 5, 0, 0, 0, 0, 0, 5, 0... | cebuaner |
4,628 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BAG-ONG', 'PANGANAK', 'NGA', 'BATANG', 'BABAYE', ',', 'NAKIT-AN', 'SULOD', 'SA', 'SAKO', 'SA', 'LOOC', ',', 'DGTE', 'Usa', 'ka', 'bag-ong', 'panganak', 'nga', 'batang', 'babaye', 'ang',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 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, 1, 2, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 1, 2, 2, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0... | cebuaner |
4,629 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['QUALIFIED', 'SENIOR', 'CITIZENS', 'SA', 'DGTE', ',', 'NAKADAWAT', 'NA', 'SA', 'ILANG', 'SOCIAL', 'PENSIONS', 'Nakadawat', 'na', 'sa', 'ilang', 'quarterly', 'pension', 'nga', 'P1,500', '... | [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, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 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] | cebuaner |
4,630 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nisulod', 'na', 'sa', 'Philippine', 'Area', 'of', 'Responsibility', '(', 'PAR', ')', 'karong', 'gabii', '(', 'Aug.', '31', ',', '2022', ')', 'ang', 'Super', 'Typhoon', '"', 'Hinnamnor.'... | [0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,631 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Niulbo', 'ang', 'sunog', 'sulod', 'mismo', 'sa', 'West', 'City', 'Elementary', 'School', 'ning', 'dakbayan', 'sa', 'Dumaguete', 'karong', 'hapon', ',', 'Agosto', '31', ',', '2022.', 'Sa... | [0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 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] | cebuaner |
4,632 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PAGSUL-OB', 'OG', 'FACE', 'MASK', ',', 'DILI', 'NA', 'MANDATORY', 'SA', 'CEBU', 'CITY', 'Gipirmahan', 'ni', 'Cebu', 'City', 'Mayor', 'Michael', 'Rama', 'karong', 'adlawa', 'ang', 'execu... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 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, 7, 0, 0, 7, 8, 8, 8, 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, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,633 | 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', 'mga', 'hulagway', 'sa', 'Phantom', 'galaxy', ',', 'usa', 'ka', 'grand-design', 'spiral', 'galaxy', 'mga', '32', 'million', 'ka', 'light-years', 'ang', '... | [0, 0, 3, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,634 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DGTE', ',', 'NAKATALA', 'OG', '5', 'KA', 'BAG-ONG', 'KASO', 'SA', 'COVID-19', ';', '2', 'PASYENTE', ',', 'NAAYO', 'NA', 'Lima', 'ka', 'bag-ong', 'kaso', 'sa', 'Covid-19', 'ang', 'natala... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 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, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,635 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DIREKTANG', 'BIYAHE', 'GIKAN', 'CEBU', 'CITY', 'NGADTO', 'SA', 'SIQUIJOR', ',', 'BUKSAN', 'NA', 'Gianunsyo', 'sa', 'SUGBO', 'URBAN', 'TRANSIT', 'INC.', 'nga', 'gidumala', 'sa', 'VTI', '... | [0, 0, 0, 5, 6, 0, 0, 5, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 5, 6, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,636 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Karong', 'adlawa', ',', 'Agosto', '30', ',', '2022', ',', 'mao', 'ang', '#', 'NationalPressFreedomDay.', 'Gideklara', 'ang', 'Agosto', '30', 'matag', 'tuig', 'nga', 'National', 'Press',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 5, 0, 0, 7, 8, 8, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,637 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['CHED', ':', 'MGA', 'ESTUDYANTENG', 'DILI', 'BAKUNADO', ',', 'PUWEDE', 'NANG', 'MAKAAPIL', 'SA', 'F2F', 'CLASSES', 'Tugutan', 'na', 'ang', 'tertiary', 'students', ',', 'faculty', 'member... | [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, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 2, 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, 5... | cebuaner |
4,638 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sakit', 'ang', 'mawad-an', 'og', 'mahal', 'sa', 'kinabuhi.', 'Karong', 'Grief', 'Awareness', 'Day', ',', 'atong', 'tabangan', 'nga', 'mapagaan', 'ang', 'kasingkasing', 'sa', 'mga', 'taw... | [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] | cebuaner |
4,639 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DSWD', 'GIPANAN-AW', 'ANG', 'PAG-EXTEND', 'SA', 'EDUCATION', 'AID', 'PAYOUT', ',', 'HOUSE-TO-HOUSE', 'DISTRIBUTION', 'Gipanan-aw', 'sa', 'Department', 'of', 'Social', 'Welfare', 'and', ... | [3, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,640 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nakuhanan', 'og', 'video', 'ni', 'Dywin', 'Tac-an', 'Lou', 'ang', 'bayanihan', 'sa', 'pag-aswat', 'og', 'usa', 'ka', 'bahay-kubo', 'sa', 'Barangay', 'Bito-on', ',', 'Clarin', ',', 'Misa... | [0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 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] | cebuaner |
4,641 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Karong', 'adlawa', ',', 'Agosto', '29', ',', '2022', ',', 'atong', 'gisaulog', 'ang', 'National', 'Heroes', 'Day', 'kon', 'Araw', 'ng', 'mga', 'Bayani', 'aron', 'hatagan', 'og', 'pagday... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 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, 7, 8, 0] | cebuaner |
4,642 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PAMILYA', 'NI', 'DAUIN', 'MAYOR', 'GALIC', 'TRUITA', ',', 'GI-HOSTAGE', 'SULOD', 'MISMO', 'SA', 'ILANG', 'BALAY', 'APAN', 'LUWAS', 'NA', 'Gi-hostage', 'ang', 'asawa', 'ug', 'mga', 'anak... | [0, 0, 5, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 1, 2, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 5, 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, 0, 0, 0, 0, 0, 1, 2, 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... | cebuaner |
4,643 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Taas-taas', 'ang', 'atong', 'umalabot', 'nga', 'weekend', 'tungod', 'kay', 'usa', 'ka', 'regular', 'holiday', 'karong', 'Lunes', ',', 'Agosto', '29', ',', '2022', ',', 'isip', 'pagsaulo... | [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, 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] | cebuaner |
4,644 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mao', 'kini', 'ang', 'mga', 'venue', 'diin', 'ipanghatag', 'ang', 'educational', 'cash', 'assistance', 'sa', 'DSWD', 'ugmang', 'adlawa', ',', 'Agosto', '27', ',', '2022.', 'Makadawat', ... | [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] | cebuaner |
4,645 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['ESTUDYANTE', 'SA', 'BUNTAG', ',', 'GRAB', 'DRIVER', 'SA', 'GABIE.', 'Nakakuha', 'og', 'mga', 'pagdayig', 'ang', 'istorya', 'sa', 'usa', 'ka', '52-anyos', 'nga', 'lalake', 'human', 'sa',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,646 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BALAODNON', 'NGA', 'NAGTINGUHA', 'SA', 'PAGBALIK', 'PAG-USAB', 'SA', 'DEATH', 'PENALTY', ',', 'GIDUSO', 'Giduso', 'pag-usab', 'ni', 'Surigao', 'del', 'Norte', 'Rep.', 'Robert', 'Ace', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 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, 1, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,647 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagsugod', 'na', 'ang', 'mga', 'kawani', 'ug', 'estudyante', 'sa', 'Silliman', 'University', 'sa', 'pagtukod', 'sa', 'ilang', 'tagsa-tagsa', 'ka', 'mga', 'booth', 'alang', 'sa', 'Hibala... | [0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 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, 7, 0] | cebuaner |
4,648 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['5-ANYOS', 'NGA', 'ESTUDYANTENG', 'NAWALA', ',', 'NAA', 'RA', 'DIAY', 'SA', 'LAING', 'CLASSROOM', 'Nalisang', 'ang', 'mga', 'residente', 'sa', 'Talisay', ',', 'Batangas', 'human', 'ma-re... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,649 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Inay', 'manakop', ',', 'nanghatag', 'ang', 'kapulisan', 'og', 'helmet', 'ngadto', 'sa', 'mga', 'motorista', 'sa', 'National', 'Highway', ',', 'South', 'Road', ',', 'Barangay', 'Masaplod... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 3, 0, 0, 1, 2, 0, 0, 3, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7... | cebuaner |
4,650 | 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', 'estudyante', 'ang', 'nagsuot', 'og', 'shoe', 'coats', 'o', 'footwear', 'aron', 'magpabiling', 'luwas', 'ug', 'uga', 'ang', 'mga', 'classrooms', 'sa', 'Concepcion'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,651 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Tungod', 'sa', 'kakulang', 'sa', 'mga', 'learning', 'facilities', ',', 'usa', 'ka', 'public', 'school', 'teacher', 'sa', 'Tanjay', 'City', ',', 'Negros', 'Oriental', 'ang', 'gihimo', 'a... | [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, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,652 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'PNP', ',', 'GIIMBESTIGARAN', 'NA', 'ANG', 'MGA', 'TAHO', 'SA', 'GIINGONG', 'KIDNAPPING', 'NGA', 'NAG-VIRAL', 'ONLINE', 'Gitan-aw', 'ug', 'gitun-an', 'na', 'karon', 'sa', 'k... | [3, 4, 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, 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, 0, 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, 0, 0... | cebuaner |
4,653 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['HAPSAY', ',', 'MALINAWON', ''', 'ANG', 'UNANG', 'ADLAW', 'SA', 'KLASE', 'BISAN', 'PA', 'SA', 'TAHO', 'SA', 'PAGHUOT', ',', 'KAKULANG', 'SA', 'CLASSROOMS', 'Gihulagway', 'sa', 'Departmen... | [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, 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, 0, 0, 0, 0, 0, 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, 1... | cebuaner |
4,654 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PH', 'POVERTY', ':', 'DILI', 'KA', '"', 'FOOD', 'POOR', '"', 'KUNG', 'MOGASTO', 'KA', 'OG', 'LABAW', 'SA', 'P18.62', 'MATAG', 'KAON', 'Gipahayag', 'sa', 'Philippine', 'Statistics', 'Aut... | [5, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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... | cebuaner |
4,655 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gikompirmar', 'sa', 'Department', 'of', 'Health', '(', 'DOH', ')', 'nga', 'natala', 'niini', 'ang', 'ikaupat', 'nga', 'kaso', 'sa', 'sakit', 'nga', 'monkeypox', 'sa', 'Pilipinas.', 'Sum... | [0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 3, 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, 7, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,656 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Unang', 'adlaw', 'sa', 'face-to-face', 'classes', 'sa', 'Sibulan', 'National', 'High', 'School', 'karong', 'adlawa', ',', 'Agosto', '22', ',', '2022.', 'Mao', 'kini', 'ang', 'unang', 'h... | [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] | cebuaner |
4,657 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Moabot', 'na', 'sa', 'P1,239,000', 'ang', 'nahatag', 'nga', 'educational', 'assistance', 'sa', 'Department', 'of', 'Social', 'Welfare', 'and', 'Development', '(', 'DSWD', ')', 'sa', 'Ne... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 5, 6, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,658 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['AMPING', 'SA', 'PAG-ULAN', 'BESHIE', '!', 'Padayong', 'makasinati', 'og', 'pag-ulan', 'ang', 'Negros', 'Oriental', 'ug', 'tibuok', 'Kabisay-an', 'karong', 'adlawa', ',', 'Agosto', '22',... | [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, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,659 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'ESTUDYANTENG', 'NITRABAHO', 'SA', 'CITY', 'HALL', ',', 'NAKADAWAT', 'NA', 'SA', 'SWELDO', 'GIKAN', 'SA', 'KAGAMHANANG', 'SIYUDAD', 'Nadawat', 'na', 'sa', 'mga', 'estudyanteng', '... | [0, 0, 0, 0, 3, 4, 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, 5, 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, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 3, 0, 0, 0, 0... | cebuaner |
4,660 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Moabot', 'na', 'sa', 'P756,000', 'ang', 'nahatag', 'nga', 'educational', 'assistance', 'sa', 'Department', 'of', 'Social', 'Welfare', 'and', 'Development', '(', 'DSWD', ')', 'sa', 'Negr... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 5, 6, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,661 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Oras', 'na', 'aron', 'magsabwag', 'og', 'papremyo', 'alang', 'sa', 'Week', '6', 'sa', 'Champion', 'Na', ',', 'Milyonaryo', 'Pa'] Use the following schema: 1 = B-WIS: Beginning of a tour... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8] | cebuaner |
4,662 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Natala', 'sa', 'Pilipinas', 'ang', 'ikaduha', 'ug', 'ikatulong', 'kaso', 'niini', 'sa', 'sakit', 'nga', 'monkeypox.', 'Sumala', 'pa', 'sa', 'Department', 'of', 'Health', '(', 'DOH', ')'... | [0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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, 7, 0] | cebuaner |
4,663 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gi-share', 'ni', 'Carlo', 'Toleza', 'ngadto', 'sa', 'social', 'media', 'ang', 'usa', 'ka', 'video', 'sa', 'naglutaw', 'nga', 'sari-sari', 'store', 'sa', 'kadagatan', 'sa', 'Bais', 'City... | [0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 5, 6, 0] | cebuaner |
4,664 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'KOMPANYA', 'SA', 'SOFTDRINKS', ',', 'NIANGKON', 'NGA', 'NAMROBLEMA', 'SA', 'KAKULANGON', 'SA', 'KALAMAY', 'SA', 'NASUD', 'Giangkon', 'sa', 'mga', 'nag-unang', 'kompanyang', 'nagh... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 3, 4, 4, 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, 0, 0, 0, 0, 0, 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 |
4,665 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PASAHERO', 'NGA', 'WALA'Y', 'HELMET', ',', 'MANNEQUIN', 'MAN', 'DIAY', 'Viral', 'karon', 'ang', 'mga', 'hulagway', 'sa', 'usa', 'ka', 'delivery', 'rider', 'kinsa', 'gipahunong', 'sa', '... | [0, 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, 5, 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, 7, 0, 0, 7, 8, 8, 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... | cebuaner |
4,666 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAGTIAYON', ',', 'GIPUSIL', 'PATAY', 'SA', 'SAN', 'JOSE', 'Patay', 'ang', 'usa', 'ka', 'magtiayon', 'human', 'gipusil', 'sa', 'Purok', '3', 'sa', 'Barangay', 'Janay-Janay', 'sa', 'lungs... | [0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 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, 0, 0, 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0... | cebuaner |
4,667 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PANEL', 'SA', 'KAMARA', ',', 'GIDUSO', 'ANG', 'PAG-POSTPONE', 'NA', 'PUD', 'SA', 'BRGY', ',', 'SK', 'ELECTIONS', 'Giaprobahan', 'sa', 'suffrage', 'panel', 'ang', 'usa', 'ka', 'mosyon', ... | [0, 0, 3, 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, 3, 4, 4, 4, 4, 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, 3, 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... | cebuaner |
4,668 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Governor', 'Henry', 'Teves', ',', 'gipirmahan', 'ang', 'Medical', 'Scholar', 'sa', 'lalawigan', 'sa', 'Negros', 'Oriental', 'kagahapong', 'adlawa', ',', 'August', '15', ',', '2022.', 'A... | [0, 1, 2, 0, 0, 0, 7, 8, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0] | cebuaner |
4,669 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PULIS', ',', 'GIPUSIL', 'PATAY', 'SA', 'BAYAWAN', 'CITY', 'Patay', 'ang', 'usa', 'ka', 'pulis', 'human', 'gipusil', 'sa', 'wala', 'pa', 'mailhing', 'mga', 'suspek', 'sa', 'Barangay', 'S... | [0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,670 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gideklarar', 'sa', 'usa', 'ka', 'food', 'website', 'ang', 'Filipino', 'fast-food', 'restaurant', 'nga', 'Jollibee', 'nga', 'mao', 'ang', 'aduna'y', ''best', ''', 'fried', 'chicken', 'sa... | [0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 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, 5, 0, 5, 0, 5, 6, 0, 5, 0, 5, 0, 0, 5, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 5, 0, 5, 6, 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... | cebuaner |
4,671 | 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', 'unang', 'adlaw', 'sa', 'face-to-face', 'classes', 'sa', 'St.', 'Paul', 'University', 'Dumaguete', 'kagahapong', 'adlawa', ',', 'August', '15', ',', '2022', '.']... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,672 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Human', 'sa', 'duha', 'ka', 'tuig', 'nga', 'online', 'classes', ',', 'gi-welcome', 'sa', 'Silliman', 'University', 'pinaagi', 'sa', 'pagpabanda', 'ang', 'mga', 'estudyante', 'sa', 'unan... | [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] | cebuaner |
4,673 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PSA', ':', 'MGA', 'POBRE', 'SA', 'NASUD', ',', 'MOABOT', 'NA', 'SA', '19', 'MILYON', 'Niigo', 'sa', '18.1', '%', 'ang', 'poverty', 'incidence', 'rate', 'o', 'kapobrehon', 'sa', 'Pilipin... | [3, 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, 0, 0, 0, 7, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 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, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,674 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BALAODNON', 'NGA', 'TUMONG', 'NGA', 'KUHAAN', 'ANG', 'HOLIDAY', 'SA', 'PILIPINAS', ',', 'GIDUSO', 'Giduso', 'sa', 'House', 'of', 'Representatives', 'ang', 'usa', 'ka', 'balaodnon', 'nga... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 0, 1, 2, 0, 7, 8, 8, 8, 0, 0, 7, 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, 0, 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, 0, 7, 8, 8, 0, 0, 0, 0... | cebuaner |
4,675 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BALAODNON', 'NGA', 'MAGBAWAL', 'SA', 'PAGGAMIT', 'OG', 'CELLPHONE', 'ATOL', 'SA', 'KLASE', ',', 'GIDUSO', 'Giduso', 'sa', 'House', 'of', 'Representatives', 'ang', 'usa', 'ka', 'balaodno... | [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, 5, 0, 1, 2, 0, 7, 8, 8, 8, 0, 0, 7, 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, 0, 0, 0, 0, 0, 0, 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 |
4,676 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sigon', 'sa', 'Chinese', 'Lunar', 'Calendar', ',', 'gisaulog', 'ang', 'Ghost', 'Month', 'gikan', 'sa', 'Hulyo', '29', 'hangtod', 'Agosto', '26.', 'Matud', 'pa', 'sa', 'Chinese', 'cultur... | [0, 0, 7, 8, 8, 0, 0, 0, 7, 8, 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, 0, 0, 0, 0, 0, 0] | cebuaner |
4,677 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SENSITIBONG', 'STORYA', 'UG', 'HULAGWAY', 'GIINGONG', 'BUKOG', 'SA', 'BIKTIMA', 'SA', 'BAGYONG', 'ODETTE', ',', 'NAPALGAN', 'SA', 'USA', 'KA', 'LUNA', 'SA', 'BAIS', 'CITY', 'Napalgan', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 5, 6, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,678 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DEPED', 'SA', 'NEGROS', 'ORIENTAL', 'ANDAM', 'NA', 'SA', 'PAG-ABRI', 'SA', 'KLASE', 'KARONG', 'AGOSTO', ',', '100', '%', 'F2F', 'CLASSES', 'SA', 'NOBYEMBRE', 'Andam', 'na', 'ang', 'prob... | [3, 0, 5, 6, 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, 3, 4, 0, 0, 0, 7, 8, 8, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 1, 2, 2, 0, 0, 0, 0, 3, 4, 4, 4, 1, 2, 2, 0, 0, 0, 0, 0, 1, 2, 0, 0... | cebuaner |
4,679 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Agosto', 'pa', 'lang', 'apan', 'makita', 'na', 'sa', 'usa', 'ka', 'mall', 'ning', 'dakbayan', 'sa', 'Dumaguete', 'kining', 'mga', 'gibaligya', 'nga', 'Christmas', 'decor', 'ug', 'mga', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 7, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0] | cebuaner |
4,680 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagpahigayon', 'og', 'road', 'clearing', 'operations', 'ang', 'mga', 'kawani', 'gikan', 'sa', 'nagkalain-laing', 'hingtungdan', 'nga', 'mga', 'ahensya', 'sa', 'kadalanan', 'sa', 'dakbay... | [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, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 3, 4, 4, 0, 3, 4, 4, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,681 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BALAUDNON', 'PAGHATAG', 'OG', 'P2,000', 'AYUDA', 'SA', 'TANANG', 'PILIPINO', ',', 'GIDUSO', 'Giduso', 'karon', 'sa', 'House', 'of', 'Representatives', 'ang', 'usa', 'ka', 'balaodnon', '... | [0, 0, 0, 0, 0, 0, 0, 7, 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, 7, 0, 0, 7, 8, 8, 8, 0, 7, 8, 8, 0, 0, 0, 3, 4, 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, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0... | cebuaner |
4,682 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'MARITES', ',', 'GIDUSO', 'NGA', 'MAPRISO', 'SA', 'USA', 'KA', 'BALAUDNON', 'BATOK', 'FAKE', 'NEWS', 'Gipasaka', 'ngadto', 'sa', 'House', 'of', 'Representatives', 'ang', 'usa', 'k... | [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, 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, 0, 0, 1, 2, 2, 0, 3, 4, 4, 0, 0, 0, 0, 7, 8, 8, 8, 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, 7, 8, 8, 0, 0, 3, 4... | cebuaner |
4,683 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['EKONOMIYA', 'SA', 'PILIPINAS', ',', 'NITUBO', 'OG', '7.4', '%', 'SA', '2ND', 'QUARTER', 'SA', '2022', 'Nitubo', 'og', '7.4', 'porsiyento', 'ang', 'ekonomiya', 'sa', 'Pilipinas', 'sa', '... | [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, 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, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,684 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PILIPINONG', 'SI', 'CARDINAL', 'TAGLE', ',', 'USA', 'SA', 'GIPANAN-AW', 'NGA', 'MAHIMONG', 'SUNOD', 'NGA', 'SANTO', 'PAPA', 'Usa', 'sa', 'duha', 'nga', 'nangunang', 'pilian', 'aron', 'm... | [7, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 1, 2, 2, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0... | cebuaner |
4,685 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['WALA', 'NA'Y', 'ATRASAY', ':', 'DEPED', ',', 'NIBAROG', 'NGA', 'MAGSUGOD', 'ANG', 'KLASE', 'KARONG', 'AGOSTO', '22', 'Nagpabiling', 'lig-on', 'ang', 'desisyon', 'sa', 'Department', 'of'... | [0, 0, 0, 0, 3, 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, 0, 0, 3, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 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 |
4,686 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAPIN', 'P1.5', 'MILYON', 'SA', 'GITUOHANG', 'SHABU', ',', 'NASAKMIT', 'SA', 'KAPULISAN', 'SA', 'SIBULAN', 'Nasikop', 'sa', 'kapulisan', 'ang', 'usa', 'ka', 'lalake', 'kinsa', 'nakuhaan... | [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, 5, 6, 0, 0, 0, 5, 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, 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... | cebuaner |
4,687 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Daw', 'nahimong', 'suba', 'kini', 'nga', 'dalan', 'sa', 'Colo', ',', 'Guihulngan', 'City', 'kagabii', ',', 'Agosto', '8', ',', '2022', 'human', 'nga', 'kini', 'gibaha', 'tungod', 'sa', ... | [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] | cebuaner |
4,688 | 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', 'mga', 'pampubliko', 'ug', 'pribadong', 'eskuwelahan', 'sa', 'tibuok', 'Guihulngan', 'City', 'karong', 'adlawa', ',', 'Agosto', '9', ',', '2022.', 'Kini... | [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, 1, 2, 2, 2, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,689 | 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', 'P8', 'NGA', 'PLETE', 'SA', 'FLIGHTS', 'SA', 'ILANG', '8.8', 'SALE', 'Gianunsyo', 'sa', 'Cebu', 'Pacific', 'ang', 'ilang', 'dugang', 'nga', 'mga', '... | [3, 4, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 0, 5, 0, 5, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,690 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUL-AN', '3', 'MILYON', 'KA', 'PILIPINO', ',', 'WALAY', 'TRABAHO', 'Dul-an', 'sa', '2.99', 'milyon', 'ka', 'mga', 'Pilipino', 'ang', 'wala'y', 'trabaho', 'sa', 'bulan', 'sa', 'Hunyo', '... | [0, 0, 0, 0, 5, 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, 5, 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, 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, 1... | cebuaner |
4,691 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MANGINGISDA', 'SA', 'MANJUYOD', ',', 'NALUMOS', 'PATAY', 'Patay', 'ang', 'usa', 'ka', 'lalake', 'human', 'malumos', 'sa', 'Sitio', 'Limayag', 'sa', 'Barangay', 'Bolisong', 'sa', 'lungso... | [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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,692 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAPIN', '3,000', 'KA', 'AFTERSHOCKS', ',', 'NATALA', 'SA', 'PHIVOLCS', 'HUMAN', 'ANG', 'KUSOG', 'NGA', 'LUZON', 'EARTHQUAKE', 'Nakatala', 'ang', 'Philippine', 'Institute', 'of', 'Volcan... | [0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 7, 8, 0, 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, 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, 5, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,693 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mga', 'kompanya', 'sa', 'petrolyo', 'nagpahibalo', 'nga', 'aduna'y', 'rollback', 'sa', 'presyo', 'sa', 'gas', ',', 'epektibo', 'karong', 'Martes', ',', 'August', '9', ',', '2022'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,694 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nangita', 'karon', 'ang', 'usa', 'ka', 'online', 'candy', 'shop', 'og', 'usa', 'ka', 'professional', 'taster', 'aron', 'motilaw', 'sa', 'ilang', 'mga', 'produkto.', 'Sumala', 'pa', 'sa'... | [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, 0, 0, 0, 0, 0, 5, 6, 0, 0, 1, 2, 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, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,695 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gitanyag', 'karon', 'ang', 'bugas', 'sa', 'presyong', 'P20', 'kada', 'kilo', 'sa', 'lungsod', 'sa', 'Botolan', ',', 'Zambales.', 'Kini', 'pinaagi', 'sa', 'usa', 'ka', 'programa', 'nga',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 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... | cebuaner |
4,696 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipaubos', 'na', 'sa', 'nagkalain-laing', 'heavy', 'rainfall', 'warning', 'ang', 'Negros', 'Oriental', 'ug', 'mga', 'kasikbit', 'nga', 'probinsya', 'niini', 'tungod', 'sa', 'walay', 'pu... | [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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 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, 0, 0, 0, 0, 0, 0] | cebuaner |
4,697 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Baha', 'sa', 'Dumaguete', 'City', 'tungod', 'sa', 'mga', 'pag-ulan', 'nga', 'dala', 'sa', 'LPA', 'ug', 'Habagat.', 'Live', 'karon', 'ang', 'atong', 'Silliman', 'University', 'intern', '... | [0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 1, 2, 2, 2, 0] | cebuaner |
4,698 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sitwasyon', 'sa', 'pipila', 'ka', 'dalan', 'ning', 'dakbayan', 'sa', 'Dumaguete', 'karong', 'adlawa', 'Agosto', '7', ',', '2022', ',', 'human', 'nga', 'kini', 'gibaha', 'tungod', 'sa', ... | [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] | cebuaner |
4,699 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'CITY', ',', 'GIBAHA', 'Napuno', 'sa', 'baha', 'karon', 'ang', 'national', 'highway', 'duol', 'sa', 'Freedom', 'Park', 'ning', 'dakbayan', 'sa', 'Dumaguete', 'tungod', 'sa',... | [5, 6, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
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