Unnamed: 0 int64 0 335k | question stringlengths 17 26.8k | answer stringlengths 1 7.13k | user_parent stringclasses 29
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4,700 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PRESYO', 'SA', 'KALAMAY', ',', 'MOABOT', 'NA', 'SA', 'P100', '/', 'KILO', 'SA', 'PIPILA', 'KA', 'MERKADO', 'Moabot', 'na', 'sa', 'P100', 'kada', 'kilo', 'ang', 'presyo', 'sa', 'kalamay'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 6, 0, 5, 6, 6, 6, 6, 6, 0, 5, 6, 0, 0, 5, 6, 6, 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... | cebuaner |
4,701 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['183', 'KA', 'STREET', 'FOOD', 'VENDORS', 'SA', 'DGTE', ',', 'GIHATAGAN', 'OG', 'NEGO-KART', 'ALANG', 'SA', 'DUGANG', 'INCOME', 'Pormal', 'nga', 'gihatagan', 'sa', 'NEGO-KART', 'karong',... | [0, 0, 0, 0, 0, 0, 5, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 5, 6, 0, 1, 2, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 1, 2, 2, 0, 0, 0, 7, 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, 7... | cebuaner |
4,702 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Duha', 'ka', 'magtutudlo', 'sa', 'Negros', 'Oriental', 'ang', 'nalakip', 'sa', '28', 'nga', 'gipasidunggan', 'isip', 'Most', 'Inspiring', 'Teachers', 'of', 'the', 'Philippines', 'niadto... | [0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 3, 4, 4, 0, 0, 1, 2, 2, 0, 0, 3, 4, 0, 0, 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, 2, 0, 1, 2, 0, 1, 2, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 2, 0, 1, 2... | cebuaner |
4,703 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', ',', 'NALUMOS', 'SA', 'LUNGSOD', 'SA', 'SIBULAN', 'Nalumos', 'ang', 'usa', 'ka', 'lalaki', 'didto', 'sa', 'Purok', '5', ',', 'Barangay', 'Poblacion', 'sa', 'lungsod', 'Sibulan'... | [0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 5, 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, 0, 0, 0, 0, 0, 0, 1, 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, 5, 0, 1, 0, 0, 0, 0, 0... | cebuaner |
4,704 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['ANG', 'GIINGONG', 'BITUON', ',', 'CHORIZO', 'RA', 'DIAY', '!', 'Nangayo', 'og', 'pasaylo', 'ang', 'French', 'physicist', 'nga', 'si', 'Etienne', 'Klein', 'human', 'siya', 'nag-post', 'o... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 1, 2, 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, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0... | cebuaner |
4,705 | 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', ',', 'NIBUROT', 'NGADTO', 'SA', '6.4', '%', 'NIADTONG', 'HULYO', 'Nisaka', 'ang', 'inflation', 'rate', 'sa', 'Pilipinas', 'ngadto', 'sa', '6.4', '... | [0, 0, 0, 5, 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, 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, 0... | cebuaner |
4,706 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['9', 'KA', 'KABANAY', 'NAHILO', 'HUMAN', 'NIKAON', 'OG', 'BUTETE', ';', '1', 'PATAY', 'Patay', 'ang', 'usa', 'ka', 'inahan', 'samtang', 'gidala', 'sa', 'ospital', 'ang', 'walo', 'niya', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 3... | cebuaner |
4,707 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PAGDILI', 'SA', 'PAGBALIGYA', 'OG', 'PAGKAON', 'SA', 'VIRGIN', 'ISLAND', ',', 'GIPANAWAGAN', 'Gidili', 'sa', 'lokal', 'nga', 'kagamhanan', 'sa', 'lungsod', 'sa', 'Panglao', 'sa', 'Bohol... | [0, 0, 0, 0, 0, 0, 5, 6, 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, 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, 0, 0, 0, 0, 0, 1, 2, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0... | cebuaner |
4,708 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAN-ANAN', ',', 'NAGTANYAG', 'OG', 'LIBRENG', 'SAMGYUPSAL', 'SA', 'MGA', 'GINGANLAN', 'OG', 'NICOLE', 'Nagtanyag', 'og', 'Free', 'Unli', 'Meal', 'ang', 'Samgyeopsal', 'House', 'sa', 'Va... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 7, 8, 8, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 7, 8, 8, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,709 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SWS', ':', '48', '%', 'SA', 'MGA', 'PAMILYANG', 'PILIPINO', 'GIKONSIDERAR', 'ANG', 'ILANG', 'KAUGALINGON', 'NGA', 'KABUS', 'Nisaka', 'ang', 'porsyento', 'sa', 'mga', 'pamilyang', 'Pilip... | [0, 0, 0, 0, 0, 0, 0, 7, 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, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 3, 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, 7, 0, 0... | cebuaner |
4,710 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['REMOLLO', 'NAMES', '5', 'COUNCILORS', 'AS', 'DEPUTY', 'MAYORS', 'OF', 'DUMAGUETE', 'Dumaguete', 'City', 'Mayor', 'Felipe', 'Remollo', 'has', 'appointed', 'five', 'city', 'councilors', '... | [1, 0, 0, 0, 0, 0, 0, 0, 5, 5, 6, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 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, 3, 4, 0, 1, 2, 0, 0, 0, 0, 0, 0... | cebuaner |
4,711 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['VALIDITY', 'SA', 'BIRTH', ',', 'DEATH', ',', 'UG', 'MARRIAGE', 'CERTIFICATES', ',', 'HINGPIT', 'NGA', 'PERMANENTE', 'NA', 'Permanente', 'na', 'ang', 'validity', 'sa', 'tanang', 'mga', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 3, 4, 4... | cebuaner |
4,712 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['77-ANYOS', 'NGA', 'LALAKE', ',', 'SAMARAN', 'SA', 'PAGPANIGBAS', 'NGA', 'NAHITABO', 'SA', 'GUIHULNGAN', 'CITY', 'Samaran', 'ang', 'usa', 'ka', 'lalake', 'human', 'sa', 'pagpanigbas', 'n... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 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, 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... | cebuaner |
4,713 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BABAYE', 'NANGANAK', 'SA', 'USA', 'KA', 'PAWNSHOP', 'SA', 'CEBU', 'Nanganak', 'si', 'Malyn', 'Rufo', ',', '27-anyos', ',', 'sa', 'iyang', 'ikalima', 'nga', 'anak', 'ngadto', 'sa', 'usa'... | [0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 1, 2, 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, 1, 2, 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, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,714 | 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', 'BAYAWAN', 'CITY', 'Usa', 'ka', 'lalaki', 'ang', 'patay', 'human', 'nalumos', 'sa', 'Barangay', 'Nangka', 'sa', 'dakbayan', 'sa', 'Bayawan', ... | [0, 0, 0, 0, 0, 5, 6, 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, 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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,715 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['#', '4', 'MOST', 'WANTED', 'PERSON', 'SA', 'BAYAWAN', ',', 'NASIKOP', 'SA', 'KAPULISAN', 'Nasikop', 'sa', 'kapulisan', 'ang', 'ika-upat', 'sa', 'listahan', 'sa', 'Most', 'Wanted', 'Pers... | [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, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 5, 6, 0, 5, 6, 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, 7, 8, 8, 8, 0, 0, 0, 7, 8, 8, 8... | cebuaner |
4,716 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'PATAY', 'SA', 'GIINGONG', 'PAGPAMUSIL', 'SA', 'VALLEHERMOSO', 'Usa', 'ang', 'patay', 'sa', 'giingong', 'pagpamusil', 'nga', 'nahitabo', 'sa', 'Barangay', 'Poblacion', 'sa', 'l... | [0, 0, 0, 0, 0, 0, 5, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,717 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nakatala', 'na', 'ang', 'Phivolcs', 'og', '2,010', 'ka', 'aftershocks', 'sa', 'nagkalain-laing', 'bahin', 'sa', 'Luzon', 'human', 'ang', 'kusog', 'nga', 'magnitude', '7', 'nga', 'linog'... | [0, 0, 0, 3, 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, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,718 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nitaliwan', 'na', 'sa', 'laing', 'kalibutan', 'si', 'kanhing', 'Presidente', 'Fidel', 'V.', 'Ramos.', 'Mao', 'kini', 'ang', 'gikompirmar', 'sa', 'Malacañang', 'karong', 'adlawa', ',', '... | [0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0] | cebuaner |
4,719 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Magpabilin', 'gihapon', 'ang', 'Negros', 'Oriental', 'ubos', 'sa', 'Alert', 'Level', '2', 'karong', 'Agosto', '1', 'hangtod', '15', ',', '2022', ',', 'sumala', 'pa', 'sa', 'Department',... | [0, 0, 0, 5, 6, 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] | cebuaner |
4,720 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dakong', 'garbo', 'karon', 'sa', 'dakbayan', 'sa', 'Dumaguete', 'ang', 'mga', 'batan-ong', 'arnisador', 'nga', 'nag-uli', 'og', 'mga', 'nagkalain-laing', 'medalya', 'gikan', 'sa', '16th... | [0, 0, 0, 0, 0, 0, 5, 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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0... | cebuaner |
4,721 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KONSUMIDOR', ',', 'NAKURATAN', 'SA', 'IYANG', '₱6', 'MILLION', 'NGA', 'BAYRONON', 'SA', 'KURYENTE', 'Nag-viral', 'sa', 'social', 'media', 'ang', 'post', 'sa', 'usa', 'ka', 'konsumidor',... | [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, 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, 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 |
4,722 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', ',', 'GIPUSIL', 'PATAY', 'SA', 'GIINGONG', 'RIDING-IN-TANDEM', 'LUNGSOD', 'SA', 'ZAMBOANGUITA', 'Gipusil-patay', 'ang', 'usa', 'ka', 'lalaki', 'sa', 'giingong', 'riding-in-tand... | [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, 5, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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... | cebuaner |
4,723 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['20-ANYOS', 'NGA', 'LALAKI', 'SA', 'SIATON', ',', 'NALUMOS', 'PATAY', 'Natapos', 'sa', 'trahedya', 'ang', 'sadya', 'unta', 'nga', 'pag-inom', 'sa', 'mga', 'paryente', 'human', 'nalumos-p... | [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, 1, 2, 2, 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, 0, 0, 0, 0, 0, 0... | cebuaner |
4,724 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LIBRENG', 'DIALYSIS', 'ALANG', 'SA', 'MGA', 'KABUS', ',', 'GIDUSO', 'KARON', 'SA', 'KAMARA', 'Giduso', 'karon', 'sa', 'Kamara', 'ang', 'usa', 'ka', 'balaodnon', 'pagmando', 'sa', 'tanan... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 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, 5, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,725 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SUGOD', 'KARONG', 'OKTUBRE', '2022', ':', 'NORECO', 'II', ',', 'MAMUTOL', 'NA', 'OG', 'ACCOUNTS', 'NGA', '1', 'KA', 'BULAN', 'NANG', 'WALA', 'GIBAYRAN', 'Ipatuman', 'na'g', 'balik', 'sa... | [0, 0, 0, 0, 0, 3, 4, 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, 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, 7, 0] | cebuaner |
4,726 | 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', 'GITIGBAS', 'SA', 'PAMPLONA', 'Usa', 'ka', 'lalaki', 'ang', 'gitigbas', 'patay', 'sa', 'Barangay', 'Abante', 'sa', 'lungsod', 'sa', 'Pamplona', 'niadtong', 'M... | [0, 0, 0, 0, 0, 5, 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, 1, 2, 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, 1, 2, 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, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0... | cebuaner |
4,727 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['USA', 'KA', 'ORGANISASYON', 'SA', 'NEGOR', ',', 'NANGAYO', 'OG', 'HUSTISYA', 'SA', 'PAMILYANG', 'JACOLBE', 'Nanawagan', 'og', 'hustisya', 'ang', 'grupong', 'Kabataan', 'Para', 'sa', 'Ka... | [0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 3, 4, 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, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 3, 4, 4, 0, 0, 0... | cebuaner |
4,728 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['5', 'PATAY', ',', '64', 'NASAMDAN', 'SA', 'KUSOG', 'NGA', 'LINOG', 'SA', 'LUZON', 'Moabot', 'na', 'sa', 'lima', 'ang', 'gikatahong', 'namatay', 'ug', '64', 'ang', 'naangol', 'sa', 'kuso... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 5, 0, 0, 0, 5, 0, 0, 0, 5, 0, 0, 0, 0, 0, 5, 6, 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, 5, 0, 0... | cebuaner |
4,729 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'NGA', 'DUNA'Y', 'KASO', 'SA', 'GIDILING', 'DRUGAS', ',', 'NASIKOP', 'SA', 'KADALANAN', 'SA', 'DUMAGUETE', 'Gi-aresto', 'sa', 'kapulisan', 'si', 'Felix', 'Adalim', 'Tubil', 'ki... | [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, 0, 0, 0, 7, 8, 0, 7, 8, 8, 8, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,730 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PILIPINAS', 'GIILA', 'ISIP', 'USA', 'SA', 'MGA', 'PINAKA-STRESSED', ',', ''ANGRIEST', ',', ''', 'UG', ''SADDEST', ''', 'NGA', 'NASUD', 'SA', 'ASEAN', 'Giila', 'ang', 'Pilipinas', 'isip'... | [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, 0, 0, 0, 0, 0, 0, 5, 6, 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... | cebuaner |
4,731 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['2', 'KA', 'GIINGONG', 'NPA', 'PATAY', 'SA', 'PINUSILAY', 'BATOK', 'SA', 'MILITAR', 'SA', 'CANLAON', 'Patay', 'ang', 'duha', 'ka', 'giingong', 'sakop', 'sa', 'New', 'People', ''s', 'Army... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 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, 0, 1, 2, 0, 0, 0, 0, 0, 0, 3, 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] | cebuaner |
4,732 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'NGA', 'GIINGONG', 'HUBOG', 'SA', 'GUIHULNGAN', 'CITY', ',', 'NALUMOS', 'PATAY', 'Patay', 'ang', 'usa', 'ka', 'lalaki', 'human', 'nalumos', 'samtang', 'naligo', 'sa', 'suba', '... | [0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 1, 2, 2, 0, 0, 0, 0, 0, 0, 5, 6, 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, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,733 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAPIN', 'P1.9', 'MILLION', 'SA', 'GITUOHANG', 'SHABU', ',', 'NAKUMPISKAR', 'SA', 'KAPULISAN', 'SA', 'BUY-BUST', 'OPERATION', 'SA', 'BRGY.', 'BAGACAY', 'Narekober', 'sa', 'kapulisan', 'a... | [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, 5, 6, 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, 5, 6, 6, 6, 0, 0, 1, 2, 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... | cebuaner |
4,734 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagtanyag', 'karon', 'ang', 'AirAsia', 'nagtanyag', 'og', 'piso', 'sale', 'sa', 'pipila', 'ka', 'domestic', 'flights', 'niini.', 'Lakip', 'sa', 'mga', 'destinasyon', 'nga', 'gilangkuban... | [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, 5, 0, 5, 0, 5, 0, 0, 5, 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, 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] | cebuaner |
4,735 | 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', 'World', 'Health', 'Organization', '(', 'WHO', ')', 'ang', 'sakit', 'nga', 'monkeypox', 'isip', 'usa', 'ka', 'public', 'health', 'emergency', 'of', 'internation... | [0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 7, 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] | cebuaner |
4,736 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'unang', 'higayon', 'sukad', 'nagsugod', 'ang', 'pandemya', 'sa', '#', 'COVID19', ',', 'kompirmadong', 'mobalik', 'na', 'sab', 'ang', 'mga', 'kalihokan', 'pagsaulog', 'sa', 'MassKa... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 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, 5, 6, 6, 0, 0, 0] | cebuaner |
4,737 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gilaoman', 'na', 'sab', 'ang', 'lain', 'na', 'pud', 'nga', 'pag-ubos', 'sa', 'presyo', 'sa', 'lana', 'sunod', 'semana', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,738 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'GIPUSIL', 'PATAY', 'SA', 'BARANGAY', 'CADAWINONAN', ',', 'DUMAGUETE', 'CITY', 'Patay', 'ang', 'usa', 'ka', 'lalaki', 'sa', 'Kalye', '2', ',', 'Housing', 'Project', ',', 'Baran... | [0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 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, 1, 2, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0... | cebuaner |
4,739 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'KANHING', 'REBELDE', ',', 'NAKADAWAT', 'OG', 'AYUDA', 'GIKAN', 'SA', 'GOBYERNO', 'SA', 'NEGOR', 'Walo', 'ka', 'mga', 'kanhing', 'rebelde', '(', 'FRs', ')', 'ang', 'nakadawat', 'o... | [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, 5, 6, 0, 0, 0, 0, 7, 8, 8, 8, 8, 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, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0... | cebuaner |
4,740 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['2', 'KA', 'GAMER', 'SA', 'CHINA', ',', 'NAGPAKULATA', 'ARON', 'MAKABAKASYON', 'Duha', 'ka', 'gamers', 'nga', 'aduna'y', 'sikat', 'nga', 'live', 'streams', 'sa', 'China', 'ang', 'giingon... | [0, 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, 0, 0, 0, 3, 4, 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... | cebuaner |
4,741 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GIINGONG', 'KALABIRA', 'SA', 'TAWO', ',', 'NAPALGAN', 'SA', 'LUNGSOD', 'SA', 'SIBULAN', 'Nakuratan', 'ang', 'pipila', 'ka', 'residente', 'sa', 'Purok', '1', ',', 'Barangay', 'Bolocboloc... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 5, 6, 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, 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, 5, 0, 0, 0] | cebuaner |
4,742 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['IBON', ':', 'MATAG', 'PILIPINO', 'ADUNA'Y', 'UTANG', 'NGA', 'P112,000', 'TUNGOD', 'SA', 'P12.5-TRILYON', 'NGA', 'UTANG', 'SA', 'PILIPINAS', 'Aduna'y', 'utang', 'nga', 'kapin', 'P112,000... | [0, 0, 0, 7, 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, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 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... | cebuaner |
4,743 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LANGYAW', 'NGA', 'BANA', 'SA', 'NURSE', 'NGA', 'NAPALGANG', 'PATAY', 'SA', 'VALENCIA', ',', 'NI-SURRENDER', 'SA', 'NBI', 'Boluntaryo', 'nga', 'mitahan', 'sa', 'buhatan', 'sa', 'National... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 3, 0, 7, 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, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0... | cebuaner |
4,744 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['VACCINATIONS', 'UG', 'COVID-19', 'TESTS', ',', 'DILI', 'NA', 'KINAHANGLAN', 'ARON', 'MAKASULOD', 'SA', 'SILLIMAN', 'CAMPUS', 'Gilibkas', 'na', 'sa', 'Silliman', 'University', '(', 'SU',... | [0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 3, 4, 4, 4, 4, 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, 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, 0, 0... | cebuaner |
4,745 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MODERN', 'BUSES', 'SA', 'DUMAGUETE', ',', 'NAG-ARANGKADA', 'NA', 'Nagsugod', 'na', 'og', 'pasada', 'karon', 'ang', 'mga', 'modernong', 'public', 'utility', 'vehicles', '(', 'PUV', ')', ... | [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, 5, 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] | cebuaner |
4,746 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DEPED', 'EXEC', ':', 'ENGLISH', ',', 'FILIPINO', 'GAMITON', 'ISIP', 'MEDIUM', 'OF', 'INSTRUCTION', 'SA', 'KINDERGARTEN', 'Kinahanglan', 'nga', 'gamiton', 'ang', 'English', 'ug', 'Filipi... | [3, 0, 0, 7, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 7, 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, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0... | cebuaner |
4,747 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MILITAR', 'UG', 'GIINGONG', 'MGA', 'NPA', 'NAGPINUSILAY', 'SA', 'GUIHULNGAN', 'CITY', ',', '1', 'GIKATAHONG', 'PATAY', 'Usa', 'ka', 'giingong', 'miyembro', 'sa', 'New', 'People', ''s', ... | [0, 0, 0, 0, 0, 0, 0, 5, 6, 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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 3, 4, 0, 0, 0, 3, 0, 5, 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, 0, 3, 0... | cebuaner |
4,748 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAG-UYAB', 'GIATAKE', 'SAMTANG', 'NAG-DATE', ';', 'LALAKE', 'GIDUNGGAB', 'PATAY', ',', 'BABAYE', 'GIINGONG', 'GILUGOS', 'SA', 'USA', 'KA', 'SUSPEK', 'Usa', 'ka', '24-anyos', 'nga', 'del... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 1... | cebuaner |
4,749 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['UNANG', 'DUHA', 'KA', 'KASO', 'SA', 'MAKAMATAY', 'NGA', 'MARBURG', 'VIRUS', ',', 'NAILA', 'SA', 'GHANA', ',', 'AFRICA', 'Gibutyag', 'sa', 'mga', 'awtoridad', 'sa', 'kahimsog', 'sa', 'Gh... | [0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 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, 7, 8, 0, 0, 7, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 7... | cebuaner |
4,750 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['TULFO', ':', '1.3', 'MILYON', 'KA', 'BENEPISYARYO', 'SA', '4Ps', ',', 'TAKTAKON', 'Gitakdang', 'taktakon', 'sa', 'Department', 'of', 'Social', 'Welfare', 'and', 'Development', '(', 'DSW... | [1, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 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, 7, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,751 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAGLULUBI', ',', 'GIPUSIL', 'PATAY', 'SA', 'BAYAWAN', 'CITY', 'Patay', 'ang', 'usa', 'ka', 'maglulubi', 'human', 'siya', 'gipusil', 'sa', 'wala', 'pa', 'mailhing', 'maumuno', 'sa', 'Sit... | [0, 0, 0, 0, 0, 5, 6, 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, 1, 2, 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, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0... | cebuaner |
4,752 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['7', 'KA', 'BALAY', 'NAIGO', 'SA', 'SUNOG', 'SA', 'AMLAN', 'Dili', 'momenos', 'sa', '7', 'ka', 'balay', 'ang', 'naigo', 'sa', 'sunog', 'nga', 'niulbo', 'sa', 'Barangay', 'Tandayag', 'sa'... | [0, 0, 0, 0, 0, 0, 0, 5, 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, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 1, 2, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 2, 0, 1, 2, 0, 1, 2, 2, 0, 0, 0, 3, 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... | cebuaner |
4,753 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['RAFFY', 'TULFO', 'NAGTANYAG', 'OG', 'P1', 'MILLION', 'REWARD', 'SA', 'PAGKASIKOP', 'SA', 'BOAC', 'CAMPING', 'KILLER-RAPIST', 'Usa', 'ka', 'senador', 'ang', 'nitanyag', 'og', 'P1', 'mily... | [1, 2, 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, 5, 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, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,754 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gibutyag', 'sa', 'Food', 'and', 'Drug', 'Administration', '(', 'FDA', ')', 'bag-ohay', 'lang', 'nga', 'dunay', 'nakitang', 'ethylene', 'oxide', 'sa', 'Lucky', 'Me', '!', 'Pancit', 'Cant... | [0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 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, 3, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 7, 8, 8, 8, 8, 0, 7, 8, 8, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,755 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KADAGHANAN', 'SA', 'MGA', 'PILIPINO', ',', 'NAGSALIG', 'SA', 'RESULTA', 'SA', 'PINILIAY', 'NIADTONG', 'MAYO', 'Gibutyag', 'sa', 'Pulse', 'Asia', 'nga', 'nagsalig', 'ang', 'kadaghanan', ... | [0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 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, 0, 0, 0, 5, 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... | cebuaner |
4,756 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DIARRHEA', 'OUTBREAK', 'SA', 'DAVAO', 'CITY', ':', '43', 'GIDALA', 'SA', 'OSPITAL', 'HUMAN', 'GIKALIBANGA', 'Naalarma', 'ang', 'mga', 'opisyal', 'sa', 'kahimsog', 'sa', 'Davao', 'City',... | [0, 0, 0, 5, 6, 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, 0, 5, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,757 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dili', 'required', 'ang', 'pagsul-ob', 'og', 'uniform', 'alang', 'sa', 'mga', 'tinun-an', 'sa', 'mga', 'pampublikong', 'eskuwelahan', 'karong', 'School', 'Year', '2022-2023', ',', 'suma... | [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, 5, 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, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,758 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PULSE', 'ASIA', ':', 'HALOS', 'KATUNGA', 'SA', 'MGA', 'PINOY', 'ANG', ''WALA', 'NALIPAY', ''', 'SA', 'K-12', 'SYSTEM', 'Dul-an', 'sa', 'katunga', 'sa', 'mga', 'Pilipino', 'ang', '"', 'd... | [3, 4, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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, 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, 4, 4, 0... | cebuaner |
4,759 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Maayong', 'balita', 'alang', 'sa', 'mga', 'motorista', ':', 'magpatuman', 'og', 'dinagko', 'nga', 'oil', 'price', 'rollback', 'ang', 'mga', 'gasolinahan', 'ugma', ',', 'July', '19', ','... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,760 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PHLPOST', ',', 'NIAWHAG', 'SA', 'PUBLIKO', 'NGA', 'PASENSYAHAN', 'ANG', 'DELAY', 'SA', 'NATIONAL', 'ID', 'Nihangyo', 'sa', 'publiko', 'ang', 'kadagkuan', 'sa', 'Philippine', 'Postal', '... | [3, 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, 3, 0, 1, 2, 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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0] | cebuaner |
4,761 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'OBESE', 'NGA', 'PINOY', ',', 'MOABOT', 'SA', '37', 'MILLION', 'Gibutyag', 'sa', 'National', 'Nutrition', 'Council', '(', 'NNC', ')', 'niadtong', 'Biyernes', ',', 'July', '15', ',... | [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, 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, 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... | cebuaner |
4,762 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dokumentaryo', 'nga', 'nagsaysay', 'sa', 'kaanindot', 'sa', 'Marawi', 'City', 'sa', 'wala', 'pa', 'ang', 'Marawi', 'siege', ',', 'nasulod', 'sa', 'Top', '15', 'sa', '#', 'MSFF2022'] Use... | [0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 7] | cebuaner |
4,763 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Filmmaker', 'nga', 'nakadawat', 'na', 'og', 'daghang', 'mga', 'awards', ',', 'magpakita', 'na', 'usab', 'sa', 'usa', 'sa', 'iyang', 'mga', 'dokumentaryo', 'sa', 'MSFF', '2022', '#', 'MS... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 7] | cebuaner |
4,764 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Opisyal', 'nang', 'gideklarar', 'sa', 'Food', 'and', 'Drug', 'Administration', '(', 'FDA', ')', 'nga', 'luwas', 'gyud', 'kan-on', 'ang', 'mga', 'produkto', 'sa', 'Lucky', 'Me', '!', 'di... | [0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 5, 0, 0, 0, 5, 0, 0, 0, 0, 1, 2, 0, 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, 0, 7, 8, 8, 8, 8, 8, 8, 8, 0, 7, 8, 8, 0, 7, 8, 8, 0, 7, 8, 8, 8, 0, 0, 0... | cebuaner |
4,765 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PDEA', ':', '359', 'KA', 'BRGY', 'SA', 'NEGOR', ',', 'APEKTADO', 'GIHAPON', 'SA', 'DROGA', 'Gibutyag', 'sa', 'Philippine', 'Drug', 'Enforcement', 'Agency', '(', 'PDEA', ')', 'nga', '359... | [3, 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, 3, 4, 4, 4, 4, 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, 1, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0... | cebuaner |
4,766 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['VP', 'SARA', ':', 'MAGSUGOD', 'ANG', 'KLASE', 'KARONG', 'AUGUST', '22', 'Gisubli', 'ni', 'Vice', 'President', 'ug', 'Education', 'Secretary', 'Sara', 'Duterte', 'nga', 'magsugod', 'ang'... | [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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,767 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DOH', 'GITUN-AN', 'ANG', 'DENGUE', 'VACCINES', 'SAMTANG', 'NAGKATAAS', 'ANG', 'MGA', 'KASO', 'NIINI', 'SA', 'NASUD', 'Gitinguha', 'sa', 'Department', 'of', 'Health', '(', 'DOH', ')', 'n... | [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, 0, 0, 0, 3, 0, 1, 2, 2, 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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,768 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['15,000', 'KA', 'PULIS', ',', 'SUNDALO', 'I-DEPLOY', 'SA', 'KINAUNAHANG', 'SONA', 'NI', 'PBBM', 'Duna'y', '15,000', 'ka', 'pulis', ',', 'sundalo', ',', 'ug', 'uban', 'pang', 'security', ... | [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, 7, 8, 8, 8, 8, 8, 8, 8, 0, 0, 1, 2, 2, 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, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0... | cebuaner |
4,769 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nag-anunsyo', 'ang', 'kagamhanang', 'lungsod', 'sa', 'La', 'Libertad', 'nga', 'maghatag', 'kini', 'og', 'libreng', 'abono', 'sa', 'mga', 'mag-uuma', 'didto.', 'Dunay', 'gigahin', 'nga',... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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... | cebuaner |
4,770 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MOST', 'WANTED', 'SA', 'SAN', 'JOSE', 'TUNGOD', 'SA', 'KASONG', 'RAPE', ',', 'NADAKPAN', 'Nasikop', 'na', 'sa', 'kapulisan', 'sa', 'San', 'Jose', 'ang', 'most', 'wanted', 'nga', 'person... | [0, 0, 0, 5, 6, 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, 1, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 1, 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, 5, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,771 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PBBM', ':', 'NATIONAL', 'ID', ',', 'POSIBLENG', 'MAGAMIT', 'NA', 'SUGOD', 'SUNOD', 'TUIG', 'Target', 'karon', 'sa', 'administrasyon', 'ni', 'Presidente', 'Ferdinand', 'Marcos', 'Jr.', '... | [1, 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, 1, 0, 0, 3, 0, 1, 2, 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, 7, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0... | cebuaner |
4,772 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['2', 'PATAY', 'HUMAN', 'MATUMBAHAN', 'OG', 'LUBI', 'SA', 'BAYAWAN', 'CITY', 'Patay', 'ang', 'duha', 'ka', 'biktima', ',', 'lakip', 'ang', 'usa', 'ka', '2-anyos', 'nga', 'bata', ',', 'hum... | [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, 5, 6, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0... | cebuaner |
4,773 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Naugdaw', 'ang', 'usa', 'ka', 'balay', 'sa', 'Purok', 'Orchids', ',', 'Daang', 'Taytayan', ',', 'Brgy', 'Calindagan', ',', 'Dumaguete', 'City', 'karong', 'hapona', ',', 'July', '14', ',... | [0, 0, 0, 0, 0, 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, 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, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,774 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sunog', 'sa', 'Purok', 'Orchids', ',', 'Daang', 'Taytayan', ',', 'Sitio', 'Canday-ong', ',', 'Barangay', 'Calindagan', ',', 'Dumaguete', 'City', 'Live', 'karon', 'ang', 'atong', 'Sillim... | [0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 3, 4, 0, 0, 0, 1, 2] | cebuaner |
4,775 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAGBABALAOD', ':', 'MGA', 'TEACHER', ',', 'WALA'Y', 'IGONG', 'PAHUWAY', 'SA', 'BAG-ONG', 'KALENDARYO', 'SA', 'DEPED', 'Nabalaka', 'si', 'Alliance', 'of', 'Concerned', 'Teachers', '(', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 1, 2, 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, 1, 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... | cebuaner |
4,776 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Moabot', 'sa', '85', 'ka', 'bags', 'sa', 'dugo', 'ang', 'gidonar', 'sa', 'mga', 'sakop', 'sa', 'Negros', 'Oriental', 'Provincial', 'Police', 'Office', '(', 'NORPPO', ')', 'atol', 'sa', ... | [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, 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, 3, 4, 4, 4, 4, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0... | cebuaner |
4,777 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PRES.', 'MARCOS', ',', 'WALA', 'NA'Y', 'SINTOMAS', 'SA', 'COVID-19', 'Wala', 'nay', 'gipakita', 'nga', 'sintomas', 'sa', 'COVID-19', 'si', 'Presidente', 'Ferdinand', 'Marcos', 'Jr.', 'u... | [0, 1, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 7, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0... | cebuaner |
4,778 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['CHED', 'DILI', 'MAGMANDO', 'OG', '100', '%', 'F2F', 'CLASSES', 'SA', 'MGA', 'UNIBERSIDAD', ',', 'KOLEHIYO', 'Dili', 'magmando', 'ang', 'Commission', 'on', 'Higher', 'Education', '(', 'C... | [3, 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, 1, 2, 2, 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... | cebuaner |
4,779 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PIMENTEL', ',', 'NIHANGYO', 'SA', 'BSP', 'NGA', 'SUSPENSUHON', 'ANG', ''IMPRACTICAL', ''', 'NGA', 'P1,000', 'POLYMER', 'BILLS', 'Nihangyo', 'si', 'Senador', 'Aquilino', '“Koko”', 'Pimen... | [1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 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, 1, 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, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,780 | 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', '4', 'KA', 'BAG-ONG', 'KASO', 'SA', 'COVID-19', 'Gikumpirma', 'sa', 'City', 'Health', 'Office', 'ang', 'pagkaayo', 'sa', 'usa', 'ka', '61-anyos', 'nga', 'n... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 3, 4, 4, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,781 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Sen.', 'Sonny', 'Angara', 'maoy', 'tagsulat', 'sa', 'Integrated', 'Filipino-Muslim', 'and', 'Indigenous', 'Peoples', 'History', 'Act', ',', 'nga', 'nagpadayag', 'sa', 'kabatan-ona... | [0, 0, 1, 2, 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, 7, 0, 0, 0, 0] | cebuaner |
4,782 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'Victorias', 'City', 'Environmental', 'and', 'Natural', 'Resources', 'Office', 'ug', 'Philippine', 'National', 'Police', '(', 'PNP', ')', 'Traffic', 'Enforcement', 'Management', '... | [0, 3, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 7, 8, 0] | cebuaner |
4,783 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'kataas', 'sa', 'COVID-19', 'pandemic', 'dihang', 'gipatuman', 'ang', 'RA', '11561', 'o', 'Increasing', 'the', 'Bed', 'Capacity', 'sa', 'East', 'Ave.', 'Medical', 'Center', 'Act', ... | [0, 0, 0, 7, 0, 0, 0, 0, 7, 8, 0, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 1, 2, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0] | cebuaner |
4,784 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'lapida', 'ay', 'minarkahan', 'hindi', 'lamang', 'ang', '"', 'katapusan', '"', 'ng', 'kanilang', 'buhay', 'kolehiyo', ',', 'kundi', 'pati', 'na', 'rin', 'ang', 'kanilang', '"', 'w... | [0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 7, 8, 8, 0, 0, 1, 0, 0, 0, 7, 8, 8, 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, 1, 0] | cebuaner |
4,785 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'low', 'pressure', 'area', '(', 'LPA', ')', 'padayong', 'nagdala', 'og', 'ulan', 'ug', 'pagpanugdog-kilat', 'ilabi', 'na', 'sa', 'Visayas', ',', 'Mindanao', 'ug', 'Southern', 'Luz... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 5, 6, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0] | cebuaner |
4,786 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['WALAY', 'BULAK', 'BISAN', 'Trending', 'karon', 'ang', 'post', 'sa', 'Facebook', 'sa', 'netizen', 'nga', 'si', 'Crizza', 'May', 'Lazaga', 'sa', 'komedya', 'sa', 'iyang', 'mga', 'higala',... | [0, 0, 0, 0, 0, 0, 0, 0, 7, 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, 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, 1, 0] | cebuaner |
4,787 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mga', 'nakumpiska', 'nga', 'ilegal', 'nga', 'drugas', 'nagkantidad', 'og', 'P18.2', 'milyones', 'sa', 'Task', 'Force', 'Davao', 'checkpoint', 'sa', 'Barangay', 'Sirawan', ',', 'D... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0] | cebuaner |
4,788 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JUST', 'IN', ':', 'Ang', 'Philippine', 'Institute', 'of', 'Volcanology', 'and', 'Seismology', '(', 'PHIVOLCS', ')', 'nakakita', 'sa', 'pagsaka', 'sa', 'seismic', 'activity', 'sa', 'Mayo... | [0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0] | cebuaner |
4,789 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Huna-hunaa', 'ABC', 'ang', 'choices', ',', 'tapos', 'wa', 'ka', 'gipili', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a t... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,790 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'social', 'media', 'personality', 'nga', 'si', 'Toni', 'Fowler', 'mipaambit', 'sa', 'hulagway', 'uban', 'sa', ''Unkabogable', 'Star', ''', 'nga', 'si', 'Vice', 'Ganda', 'sa', 'iya... | [0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 1, 2, 0, 0, 7, 0, 0] | cebuaner |
4,791 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Base', 'sa', 'report', 'ni', 'Western', 'Visayas', 'Coast', 'Guard', 'District', 'spokesperson', 'Commander', 'Jansen', 'Benjamin', ',', 'duha', 'ka', 'insidente', 'ang', 'na-record', '... | [0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 5, 0, 0, 5, 0] | cebuaner |
4,792 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'pinakatigulang', 'sa', 'tropa', ',', 'naa', 'nay', 'early', 'signs…'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a tou... | [0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,793 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NGANONG', 'GI-UNA', 'NIMO', 'ANG', 'CONCERT', '?', 'Mao', 'kini', 'ang', 'pamahayag', 'sa', 'social', 'media', 'personality', 'nga', 'si', 'Rendon', 'Labador', 'karong', 'Domingo', ',',... | [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, 1, 2, 0, 0, 0, 0, 7, 0, 0, 0, 1, 2, 0] | cebuaner |
4,794 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Karong', 'Lunes', ',', 'Hunyo', '26', ',', 'adunay', 'adjustment', 'sa', 'presyo', 'sa', 'diesel', 'ug', 'gasolina', ',', 'matod', 'sa', 'taho.', '⬆️', 'Gasoline', '+', '0.20', '/', 'L'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,795 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Matod', 'ni', 'Department', 'of', 'Education-Region', '7', '(', 'DEPED-7', ')', 'Director', 'Salustiano', 'Jimenez', 'kaniadtong', 'Biyernes', ',', 'Hunyo', '23', ',', 'kini', 'magsilbi... | [0, 0, 3, 4, 4, 4, 4, 4, 4, 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] | cebuaner |
4,796 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Selos', 'na', 'selos', 'na', 'yern', '?', 'Tanawa', 'ko', 'sa', 'karapatan', 'bi', ',', 'naa', 'ba', '?'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 =... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,797 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['gihisgutan', 'karon', 'ang', 'pagkanselar', 'sa', 'Pride', 'PH', 'sa', 'performance', 'sa', 'OPM', 'band', 'nga', 'Silent', 'Sanctuary', 'karong', 'Sabado', ',', 'Hunyo', '24', 'sa', 'P... | [0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 7, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 7, 8, 0, 7, 8, 0, 5, 0, 0, 0, 0, 5, 6, 6, 0, 5, 6, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,798 | 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', 'gisulti', 'ni', 'Presidente', 'Bongbong', 'Marcos', 'atol', 'sa', 'paghandum', 'sa', ''Pride', 'Festival', ''', 'sa', 'miaging', 'Sabado', ',', 'Hunyo', '24.', 'Ma... | [0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0] | cebuaner |
4,799 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PADAYON', 'SA', 'LABAN', 'DAY', '!', '"', 'From', '3years', 'past', 'to', 'present', 'Dili', 'tanang', 'mga', 'pangit', 'nga', 'panghitaboan', 'kay', 'kaalaotan', 'na', 'o', 'kamalasan'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 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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