Unnamed: 0 int64 0 335k | question stringlengths 17 26.8k | answer stringlengths 1 7.13k | user_parent stringclasses 29
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4,000 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Aduna'y', 'pagsaka', 'sa', 'presyo', 'sa', 'lana', ',', 'epektibo', 'sa', 'Martes', ',', 'Hunyo', '27', ',', '2023', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-rel... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,001 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MOTORISTA', ',', 'PATAY', 'HUMAN', 'MALIGSAN', 'ANG', 'ULO', 'SA', '10-WHEELER', 'DUMP', 'TRUCK', 'Patay', 'ang', 'usa', 'ka', 'motorista', 'sa', 'usa', 'ka', 'vehicular', 'accident', '... | [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, 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, 5, 6, 6, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,002 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['9', 'KA', 'MAYOR', 'SA', 'NEGOR', ',', 'NANAWAGAN', 'NGA', 'I-POSTPONE', 'ANG', 'BARANGAY', ',', 'SK', 'ELECTION', 'Nipadayag', 'og', 'suporta', 'ang', 'siyam', 'ka', 'mga', 'mayor', 's... | [0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 2, 0, 5, 0, 0, 0, 0, 0, 1, 2, 0, 5, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0... | cebuaner |
4,003 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'SA', 'INDIA', ',', 'NIPUYO', 'OG', 'DUL-AN', '2', 'KA', 'TUIG', 'SA', 'USA', 'KA', '5-STAR', 'HOTEL', 'NGA', 'WALA’Y', 'BAYAD-BAYAD', 'Usa', 'ka', 'lalaki', 'ang', 'giimbestig... | [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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 1, 2, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,004 | 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', 'hulagyway', 'ni', 'President', 'Ferdinand', 'Marcos', 'Jr.', 'uban', 'sa', 'pipila', 'ka', 'mga', 'lokal', 'nga', 'opisyales', 'sa', 'probinsya', 'sa', 'Negros', '... | [0, 0, 0, 0, 0, 0, 1, 2, 2, 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, 1, 0, 0, 0, 5, 6, 0, 1, 2, 2, 0, 5, 0, 1, 2, 0, 0, 5, 0, 1, 2, 0] | cebuaner |
4,005 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['STATE', 'OF', 'CALAMITY', 'SA', 'TIBUOK', 'PILIPINAS', 'TUNGOD', 'SA', 'ASF', ',', 'GITUN-AN', 'Gitun-an', 'karon', 'sa', 'Department', 'of', 'Agriculture', '(', 'DA', ')', 'ang', 'pags... | [0, 0, 0, 0, 0, 5, 0, 0, 7, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 1, 2, 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, 7, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,006 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'HAYOP', 'SA', 'AMLAN', 'ZOO', ',', 'IBALHIN', 'SA', 'AKLAN', 'Dal-on', 'sa', 'usa', 'ka', 'private', 'farm', 'sa', 'Bukid', 'Tigayon', 'Kalibo', ',', 'Aklan', 'ang', 'mga', 'hayo... | [0, 0, 0, 5, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 5, 6, 6, 0, 0, 1, 2, 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] | cebuaner |
4,007 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['16', 'KA', 'BULAN', 'NGA', 'BATA', ',', 'PATAY', 'HUMAN', 'GIBIYAAN', 'OG', '8', 'KA', 'ADLAW', 'SA', 'INAHAN', 'ARON', 'MAGBAKASYON', 'Patay', 'na', 'nga', 'napalgan', 'ang', 'usa', 'k... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 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... | cebuaner |
4,008 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NEGROS', 'ORIENTAL', 'PROVINCIAL', 'HOSPITAL', ',', 'NASUPLAYAN', 'OG', 'P10-M', 'NGA', 'DUGANG', 'TAMBAL', 'Naabot', 'na', 'kagahapong', 'adlawa', 'ang', 'mga', 'stock', 'sa', 'medisin... | [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, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,009 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Wala', 'pa'y', 'nakadaog', 'sa', 'kapin', 'P292', 'milyones', 'nga', 'jackpot', 'prize', 'sa', 'Ultra', 'Lotto', '6', '/', '58.', 'Sumala', 'pa', 'sa', 'PCSO', ',', 'wala'y', 'nakakuha'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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] | cebuaner |
4,010 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GIINGONG', 'ILLEGAL', 'QUARRY', 'SA', 'NEGROS', 'ORIENTAL', ',', 'NADAKPAN', 'Nasikop', 'sa', 'Criminal', 'Investigation', 'and', 'Detection', 'Group', '(', 'CIDG-PNP', ')', 'ang', 'gii... | [0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 5, 6, 0, 1, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,011 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JOB', 'ORDER', 'UG', 'CONTRACT', 'OF', 'SERVICE', 'WORKERS', 'SA', 'DGTE', ',', 'MAKADAWAT', 'OG', '25KG', 'NGA', 'BUGAS', 'Makadawat', 'og', '25kg', 'nga', 'ayudang', 'bugas', 'ang', '... | [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, 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] | cebuaner |
4,012 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PLDT', ',', 'NAGSUGYOT', 'OG', 'PAMAAGI', 'ARON', 'MAPAKUSGAN', 'ANG', 'CCTV', 'SA', 'DUMAGUETE', ';', 'POSIBLENG', 'MAGTAOD', 'SAB', 'OG', 'PUBLIC', 'WIFI', 'UG', 'TRAFFIC', 'LIGHTS', ... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 2, 2, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,013 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BABAYI', 'SA', 'ECUADOR', 'NGA', 'NAKAMATA', 'SULOD', 'SA', 'IYANG', 'LUNGON', ',', 'TINUOD', 'NA', 'NGA', 'PATAY', 'Tinuod', 'na', 'nga', 'namatay', 'ang', 'usa', 'ka', 'tigulang', 'ng... | [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, 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, 1, 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... | cebuaner |
4,014 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LATO-LATO', 'NO', 'MORE', '!', 'Nagpahimangno', 'sa', 'publiko', 'ang', 'Food', 'and', 'Drug', 'Administration', '(', 'FDA', ')', 'nga', 'dili', 'mopalit', 'sa', 'dulaan', 'nga', 'lato-... | [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, 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] | cebuaner |
4,015 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['637', 'KA', 'EDUCATIONAL', 'SCHOLAR', 'SA', 'NEGOR', ',', 'HATAGAN', 'OG', '₱5,000', 'NGA', 'AYUDA', 'KADA', 'USA', 'Gipatuman', 'ni', 'Gov.', 'Manuel', '"', 'Chaco', '"', 'Sagarbarria'... | [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 0, 7, 8, 8, 8, 8, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,016 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DOLE-7', ',', 'GIPANGHINGUSGAN', 'ANG', 'PAG-MONITOR', 'SA', 'MGA', 'CHILD', 'LABORER', 'SA', 'NEGOR', 'Gipanghingusgan', 'sa', 'Department', 'of', 'Labor', 'and', 'Employment', 'sa', '... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 0, 3, 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, 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, 5, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 5, 0, 0... | cebuaner |
4,017 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', '42', 'anyos', 'nga', 'janitress', 'sa', 'Tuguegarao', 'City', 'ang', 'mapasigarbuhon', 'nga', 'nag-pose', 'human', 'sa', 'iyang', 'klase', 'sa', 'kindergarten.', 'Mogradwar... | [0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,018 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['ANGAY', 'NGA', 'POSTURA', 'SA', 'KAMOT', 'ATOL', 'SA', 'PAG-AMPO', 'SA', ''OUR', 'FATHER', ''', 'SA', 'MISA', 'Nagpagawas', 'og', 'usa', 'ka', 'sulat', 'ang', 'Diocese', 'of', 'Dumaguet... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 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, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,019 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PULIS', ',', 'GIPADAKOP', 'ANG', 'ASAWA', 'SAMTANG', 'KAUBAN', 'ANG', 'GIINGONG', 'KABIT', 'NIINI', 'SA', 'BACOLOD', 'CITY', 'Naabtan', 'sa', 'mga', 'awtoridad', 'ang', 'asawa', 'sa', '... | [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, 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... | cebuaner |
4,020 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', ',', 'NAPUSILAN', 'ANG', 'KAUGALINGON', 'SAMTANG', 'NAGDAMGO', 'NGA', 'GIKAWATAN', 'ANG', 'BALAY', 'Aksidenteng', 'napusilan', 'sa', 'usa', 'ka', 'lalaki', 'sa', 'Estados', 'Un... | [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, 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, 0, 0, 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 |
4,021 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BROWNOUT', 'NA', 'PUD.', 'Sa', 'ikaduhang', 'higayon', ',', 'walay', 'kuryente', 'na', 'pud', 'sa', 'tibuok', 'Dumaguete', 'City', 'ug', 'sa', 'mga', 'kasikbit', 'nga', 'lungsod', 'niin... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0] | cebuaner |
4,022 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Walay', 'kuryente', 'gihapon', 'sa', 'pipila', 'ka', 'bahin', 'sa', 'Negros', 'Oriental', 'taliwala', 'sa', 'ulan', 'nga', 'padayong', 'nasinati', 'sa', 'probinsya', 'karong', 'Huwebes'... | [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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 0] | cebuaner |
4,023 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nakadawat', 'og', 'standing', 'ovation', 'ang', 'Bisaya', 'singer', 'nga', 'si', 'Roland', '"', 'Bunot', '"', 'Abante', 'human', 'kini', 'nitungtong', 'sa', 'entablado', 'sa', 'America'... | [0, 0, 0, 0, 0, 7, 0, 0, 0, 1, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,024 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Heads', 'up', ',', 'beshy', '!', 'Walay', 'kuryente', 'karong', 'Dominggo', ',', 'Hunyo', '18', ',', '2023', ',', 'gikan', 'alas-5:30', 'sa', 'buntag', 'hangtud', 'alas-6', 'sa', 'gabii... | [0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 6, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,025 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gideklarar', 'sa', 'Malacañang', 'nga', 'regular', 'holiday', 'ang', 'Miyerkules', ',', 'Hunyo', '28', ',', '2023', ',', 'isip', 'pagsaulog', 'sa', 'Eid'l', 'Adha', 'kon', 'Feast', 'of'... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 7, 0] | cebuaner |
4,026 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Walay', 'kuryente', 'karong', 'Sabado', ',', 'Hunyo', '17', ',', '2023', ',', 'gikan', 'alas-6', 'sa', 'buntag', 'hangtud', 'alas-6', 'sa', 'gabii.', 'Usa', 'ka', 'scheduled', 'power', ... | [0, 0, 0, 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, 5, 6, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 5, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0] | cebuaner |
4,027 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LA', 'LIBERTAD', ',', 'NAG-APOD-APOD', 'OG', '25KG', 'NGA', 'BUGAS', 'SA', 'MGA', 'RESIDENTE', 'NIINI', 'NGA', 'APEKTADO', 'SA', 'ASF', 'CRISIS', 'Nag-apod-apod', 'ang', 'LGU', 'sa', 'L... | [5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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, 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, 5, 6, 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... | cebuaner |
4,028 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PARI', ',', 'PATAY', 'HUMAN', 'NIBANGGA', 'ANG', 'GIMANEHONG', 'MOTORSIKLO', 'SA', 'DUMP', 'TRUCK', 'Patay', 'ang', 'usa', 'ka', 'pari', 'human', 'aksidenteng', 'nibangga', 'ang', 'gima... | [0, 0, 0, 0, 0, 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, 0, 5, 6, 0, 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, 5, 6, 6, 6, 6, 0, 0, 0, 0, 1, 0, 3, 4, 4, 4, 4, 4, 0, 0, 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... | cebuaner |
4,029 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BABAYENG', 'GIDEKLARAR', 'NA', 'NGA', 'PATAY', 'OG', '2', 'KA', 'ADLAW', ',', 'NAPALGANG', 'BUHI', 'PA', 'DIAY', 'SULOD', 'SA', 'LUNGON', 'Usa', 'ka', 'tigulang', 'sa', 'Ecuador', 'ang'... | [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, 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, 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... | cebuaner |
4,030 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NANGITA', 'OG', 'TRABAHO', '?', 'JOB', 'FAIR', ',', 'IPAHIGAYON', 'SA', 'DUMAGUETE', 'CITY', 'KARONG', 'INDEPENDENCE', 'DAY', 'Aduna'y', 'ipahigayong', 'job', 'fair', 'karong', 'Lunes',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 5, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,031 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAYON', 'VOLCANO', ',', 'GIISA', 'NA', 'SA', 'ALERT', 'LEVEL', '3', 'Giisa', 'na', 'karon', 'ngadto', 'sa', 'Alert', 'Level', '3', 'ang', 'Mayon', 'Volcano', ',', 'sumala', 'pa', 'sa', ... | [5, 6, 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, 3, 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, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,032 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Makita', 'na', 'karon', 'ang', 'mata', 'sa', 'Severe', 'Tropical', 'Storm', 'nga', '#', 'ChedengPH', '(', '#', 'GUCHOL', ')', 'nga', 'usa', 'ka', 'timailhan', 'nga', 'mokusog', 'kini', ... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,033 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAGTIAYON', 'SA', 'MALAYSIA', 'NAGBULAG', 'TUNGOD', 'SA', 'TALAGSA-ONG', 'SAKIT', 'SA', 'DUGO', 'Usa', 'ka', 'magtiayon', 'sa', 'Malaysia', 'ang', 'nagbulag', 'human', 'nahibal-an', 'ng... | [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, 1, 2, 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... | cebuaner |
4,034 | 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', 'WALA', 'NAKABAYAD', 'OG', 'UTANG', 'SA', 'ONLINE', 'LENDING', 'APP', ',', 'GIPADALHAN', 'OG', 'BULAK', 'SA', 'PATAY', 'UG', 'LUNGON', 'Pipila', 'ka', 'indibidwal'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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... | cebuaner |
4,035 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['CANADA', ',', 'NAGTANYAG', 'OG', 'VISA-FREE', 'TRAVEL', 'SA', 'MGA', 'KWALIPIKADONG', 'PILIPINO', 'Mahimo', 'ng', 'mokuha', 'og', 'visa-free', 'air', 'travel', 'ang', 'mga', 'kwalipikad... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 7, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 7, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 7, 0, 0] | cebuaner |
4,036 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PHILIPPINE', 'AIRLINES', ',', 'NAGTANYAG', 'OG', 'P125', 'NGA', 'PLITE', 'HANGTOD', 'JUNE', '25', 'Nagtanyag', 'ang', 'Philippine', 'Airlines', 'og', 'P125', 'nga', 'one-way', 'base', '... | [3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 0, 0, 5, 6, 0, 5, 0, 5, 0, 5, 0, 0, 5, 6, 0, 0, 0, 0, 5, 0, 0, 0, 0, 5, 6, 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, 0... | cebuaner |
4,037 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['CAAP', ',', 'GIDID-AN', 'ANG', 'MGA', 'EROPLANO', 'PAGLUPAD', 'DUOL', 'SA', 'KANLAON', 'VOLCANO', 'TUNGOD', 'SA', 'ABNORMAL', 'NGA', 'KAHIMTANG', 'NIINI', 'Gidili', 'sa', 'Civil', 'Avia... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,038 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nahimo', 'nang', 'usa', 'ka', 'tropical', 'depression', 'ang', 'low', 'pressure', 'area', '(', 'LPA', ')', 'nga', 'gibantayan', 'sa', 'silangang', 'bahin', 'sa', '#', 'Visayas', ',', 's... | [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, 3, 0] | cebuaner |
4,039 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PLDT', 'NITAHO', 'NGA', 'DUNAY', 'PROBLEMA', 'SA', 'INTERNET', 'NIINI', 'Gikumpirmar', 'sa', 'PLDT', 'nga', 'nakasinati', 'ang', 'mga', 'subscriber', 'niini', 'og', 'hinay', 'nga', 'int... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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] | cebuaner |
4,040 | 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', ')', 'ang', 'gibantayang', 'aktibo', 'nga', 'LPA', 'sa', 'silangang', 'bahin', 'sa', '#', 'Visayas.', 'Ad... | [0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 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, 5, 0, 0, 0, 0, 7, 0, 3, 0] | cebuaner |
4,041 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['INDONESIAN', 'BILLIONAIRE', 'MINGDONAR', 'OG', 'P41-M', 'SA', 'PILIPINAS', 'Nagdonar', 'ang', 'usa', 'ka', 'Indonesian', 'businessman', 'og', 'kapin', 'P41', 'milyones', 'ngadto', 'sa',... | [7, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
4,042 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PAGASA', ',', 'GIBANTAYAN', 'ANG', '2', 'KA', 'LPA', 'NGA', 'ANAA', 'SA', 'GAWAS', 'SA', 'PAR', 'Gibantayan', 'karon', 'sa', 'PAGASA', 'ang', 'duha', 'ka', 'low', 'pressure', 'area', '(... | [3, 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, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 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, 5, 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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,043 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mga', 'eksena', 'sa', 'pag-abot', 'sa', 'patayng', 'lawas', 'ni', 'kanhi', 'Gob.', 'Guido', 'Reyes', 'sa', 'Negros', 'Oriental', 'karong', 'adlawa', ',', 'Hunyo', '3', ',', '2023', ',',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0] | cebuaner |
4,044 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Anaa', 'na', 'karon', 'sa', 'half-mast', 'ang', 'bandila', 'sa', 'Pilipinas', 'sa', 'Freedom', 'Park', 'atbang', 'sa', 'Negros', 'Oriental', 'Provincial', 'Capitol', 'isip', 'pahasubo',... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,045 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Duna', 'nay', 'bag-ong', 'gobernador', 'ang', 'Negros', 'Oriental.', 'Kini', 'human', 'nanumpa', 'si', 'Vice', 'Governor', 'Manuel', '"', 'Chaco', '"', 'Sagarbarria', 'isip', 'bag-ong',... | [0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
4,046 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nipanaw', 'na', 'si', 'Governor', 'Jorge', 'Carlo', 'Joan', '"', 'Guido', '"', 'Reyes', 'karong', 'adlawa', ',', 'Mayo', '31', ',', '2023.', 'Kini', 'gikumpirmar', 'ni', 'Provincial', '... | [0, 0, 0, 0, 1, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,047 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE-CVIRAA', 'MEDALISTS', ',', 'MAKADAWAT', 'OG', 'CASH', 'INCENTIVES', 'GIKAN', 'SA', 'SYUDAD', 'Nihatag', 'ang', 'City', 'Government', 'sa', 'Dumaguete', 'City', 'og', 'cash', '... | [3, 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, 3, 4, 4, 4, 4, 4, 4, 4, 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, 0, 0] | cebuaner |
4,048 | 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', 'weekend', 'sa', 'ikaduhang', 'semana', 'sunod', 'bulan', 'tungod', 'aduna'y', 'usa', 'ka', 'regular', 'holiday', 'sa', 'June', '12', ',', 'isip', 'pagsaulog... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0] | cebuaner |
4,049 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BASKETBOL', ',', 'NISANGKO', 'SA', 'RAMBOL', 'Usa', 'ka', 'kagubot', 'ang', 'nahitabo', 'sa', 'gipahigayong', 'basketball', 'game', 'sa', 'Tanjay', 'City', 'niadtong', 'Lunes', ',', 'Ma... | [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, 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] | cebuaner |
4,050 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Pipila', 'ka', 'lugar', 'sa', 'Negros', 'Oriental', 'ang', 'nagsuspenso', 'sa', 'klase', 'karong', 'Martes', ',', 'Mayo', '30', ',', '2023', ',', 'tungod', 'sa', 'pag-ulan', 'nga', 'dal... | [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, 7, 8, 8, 0] | cebuaner |
4,051 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gatusan', 'ka', 'aplikante', 'nga', 'ganahang', 'moskuwela', 'sa', 'Negros', 'Oriental', 'State', 'University', '(', 'NORSU', ')', 'ang', 'padayong', 'nagtalay', 'karon', 'gawas', 'sa',... | [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, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,052 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GATOSAN', 'KA', 'APLIKANTE', 'SA', 'NORSU', ',', 'NAGTALAY', 'GIHAPON', 'BISA’G', 'GABIING', 'DAKO', 'Tungang', 'gabii', 'na', 'apan', 'gatosan', 'gihapon', 'ka', 'estudyante', 'nga', '... | [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, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 5, 6, 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, 5, 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, 3, 0, 0, 0, 0, 0, 7, 0, 0... | cebuaner |
4,053 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DGTE', ',', 'GIPANGHINGUSGAN', 'ANG', 'PAGBAKUNA', 'SA', 'MGA', 'BATA', 'BATOK', 'MEASLES', 'UG', 'RUBELLA', 'Gipanghingusgan', 'pa', 'sa', 'City', 'Governement', 'sa', 'dakbayan', 'sa'... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 3, 0, 5, 6, 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 |
4,054 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mas', 'nikusog', 'pa', 'ang', 'Super', 'Typhoon', '#', 'Mawar', 'samtang', 'gipuntirya', 'niini', 'ang', 'kadagatan', 'sa', 'Pilipinas.', 'Dala', 'karon', 'sa', 'maong', 'bagyo', 'ang',... | [0, 0, 0, 0, 7, 8, 8, 8, 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, 5, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,055 | 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', 'P88', 'NGA', 'PLITE', 'HANGTOD', 'MAY', '27', 'Nagtanyag', 'ang', 'Cebu', 'Pacific', 'og', 'P88', 'nga', 'one-way', 'base', 'fare', 'alang', '... | [3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 5, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 5, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,056 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Makita', 'na', 'sab', 'ang', 'mata', 'sa', 'Super', 'Typhoon', '#', 'Mawar', 'human', 'niini', 'gikusokuso', 'ang', '#', 'Guam', 'kagahapong', 'adlawa.', 'Gikabalak-ang', 'mosulod', 'ki... | [0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 3, 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, 5, 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... | cebuaner |
4,057 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['TEENAGER', 'SA', 'TAIWAN', ',', 'NAPALGANG', 'PATAY', 'HUMAN', 'NAGPAKASAL', 'SA', 'LALAKI', 'NGA', 'BAG-O', 'RA', 'NIYANG', 'NAKAILA', 'Usa', 'ka', '18-anyos', 'nga', 'high', 'school',... | [0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,058 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PAGASA', ',', 'GIBANTAYAN', 'ANG', 'POSIBLENG', 'MAHIMONG', ''SUPER', 'TYPHOON', ''', 'GAWAS', 'SA', 'PAR', 'Gibantayan', 'karon', 'sa', 'PAGASA', 'ang', 'usa', 'ka', 'tropical', 'cyclo... | [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, 0, 0, 0, 0, 5, 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, 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... | cebuaner |
4,059 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PATAYNG', 'LAWAS', ',', 'NAPALGAN', 'SA', 'BAYBAYON', 'SA', 'STA.', 'CATALINA', 'Usa', 'ka', 'patayng', 'lawas', 'sa', 'tigulang', 'ang', 'nakit-an', 'sa', 'baybayon', 'sa', 'Sitio', 'T... | [0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 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, 0, 0, 5, 6, 0, 0, 0, 0, 1, 2, 2, 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, 1, 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, 0, 0, 0, 0... | cebuaner |
4,060 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'KASO', 'SA', 'ASF', 'NAKOMPIRMAR', 'SA', 'DAUIN', ',', 'PIPILA', 'KA', 'BABOY', 'SA', 'LUNGSOD', 'GIPAMATAY', 'Nagpositibo', 'sa', 'African', 'Swine', 'Fever', '(', 'ASF', ')', '... | [0, 0, 0, 7, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 5, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 7, 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... | cebuaner |
4,061 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['TRAHEDYA', 'SA', 'PALITON', 'BEACH', ':', 'BATA', 'PATAY', ',', 'BABAYE', 'ANGOL', 'SA', 'DISGRASYA', 'SA', 'BANGKA', 'SA', 'SIQUIJOR', 'Patay', 'ang', 'usa', 'ka', '6', 'anyos', 'nga',... | [0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0... | cebuaner |
4,062 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['4', 'KA', 'GIINGONG', 'NPA', 'PATAY', 'SA', 'PINUSILAY', 'SA', 'GUIHULNGAN', 'CITY', 'Upat', 'ka', 'giingong', 'sakop', 'sa', 'rebeldeng', 'New', 'People’s', 'Army', '(', 'NPA', ')', 'a... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 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, 5, 6, 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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,063 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PINAKAGULANG', 'NGA', 'IRO', 'SA', 'KALIBUTAN', ',', 'GISAULOG', 'ANG', 'IYANG', 'IKA-31', 'KA', 'BIRTHDAY', 'Bag-ohay', 'lang', 'nga', 'nagsaulog', 'sa', 'iyang', 'ika-31', 'nga', 'bir... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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... | cebuaner |
4,064 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAPIN', '7-M', 'KA', 'MGA', 'PINOY', ',', 'MAKADAWAT', 'SA', 'INFLATION', 'AYUDA', 'Kapin', 'sa', 'pito', 'ka', 'milyon', 'nga', 'mga', 'Pilipino', 'ang', 'makabenepisyo', 'sa', 'progra... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 7, 8, 8, 8, 8, 8, 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, 3, 4, 4, 4, 4, 4, 4, 4, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0] | cebuaner |
4,065 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'nigradwar', 'sa', 'Negros', 'Oriental', 'State', 'University', '(', 'NORSU', ')', 'ang', 'nabutang', 'sa', 'Rank', '6', 'sa', 'March', '2023', 'Licensure', 'Exam', 'for', '... | [0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 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] | cebuaner |
4,066 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Hustisya', 'ang', 'gipanawagan', 'sa', 'mga', 'animal', 'lovers', 'alang', 'sa', 'duha', 'ka', 'iro', 'nga', 'gipusil', 'patay', 'sa', 'Metropolitan', 'police', 'sa', 'London', ',', 'Un... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 5, 6, 6, 6, 0, 0, 0, 7, 8, 8, 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, 1, 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... | cebuaner |
4,067 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['5', 'KA', 'IRO', ',', 'PATAY', 'HUMAN', 'GIPANGHILOAN', 'Hustisya', 'ang', 'gisinggit', 'sa', 'pamilyang', 'Go', 'human', 'gihiloan', 'ang', 'ilang', 'lima', 'ka', 'iro', 'sa', 'wala', ... | [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, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,068 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKING', 'HUBOG', ',', 'GIPUSIL', 'PATAY', 'SA', 'SAN', 'JOSE', 'Usa', 'ka', 'lalaking', 'gituohang', 'lango', 'sa', 'ilimnong', 'makahubog', 'ang', 'gipusil', 'patay', 'sa', 'Baranga... | [0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 2, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0... | cebuaner |
4,069 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['OFW', 'SA', 'HONG', 'KONG', ',', 'PATAY', 'HUMAN', 'MAHULOG', 'SA', 'BINTANA', 'SA', '18-FLOOR', 'BUILDING', 'Usa', 'ka', '38-anyos', 'nga', 'Overseas', 'Filipino', 'Worker', '(', 'OFW'... | [3, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 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, 3, 4, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 5, 6, 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... | cebuaner |
4,070 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['HILABIHANG', 'KAINIT', 'SA', 'PANAHON', ',', 'GIBANABANANG', 'MOLUNGTAD', 'SA', 'SUNOD', 'NGA', '5', 'KA', 'TUIG', ':', 'UN', 'Sigurado', 'nga', 'ang', '2023', 'hangtod', '2027', 'mao',... | [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, 3, 4, 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, 3, 4, 4, 4, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,071 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MGA', 'NAMATAY', 'SA', 'BABOY', 'SA', 'DAUIN', ',', 'NEGATIBO', 'SA', 'AFRICAN', 'SWINE', 'FEVER', 'Negatibo', 'sa', 'African', 'Swine', 'Fever', '(', 'ASF', ')', 'ang', 'mga', 'namatay... | [0, 0, 0, 0, 0, 5, 0, 0, 0, 7, 8, 8, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 5, 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, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 7, 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... | cebuaner |
4,072 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['FOREIGNER', ',', 'NAPALGANG', 'PATAY', 'SA', 'BACONG', 'Napalgang', 'patay', 'ang', 'usa', 'ka', 'American', 'national', 'sa', 'giabangang', 'apartment', 'niini', 'sa', 'Purok', '4', ',... | [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 1, 2, 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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,073 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LAING', 'ESTUDYANTE', 'SA', 'TANJAY', ',', 'NAKUYAPAN', 'TUNGOD', 'SA', 'GRABENG', 'KAINIT', 'Laing', 'estudyante', 'sa', 'Tanjay', 'National', 'High', 'School', '(', 'Opao', ')', 'ang'... | [0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,074 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'usa', 'ka', 'video', ',', 'gihatagan', 'ni', 'Christian', 'Mar', 'ang', 'iyang', 'asawa', 'nga', 'si', 'Roviedelia', 'Soriano', 'Villenia', 'og', 'bouquet', 'nga', 'ginama', 'sa',... | [0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0] | cebuaner |
4,075 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['CONG.', 'TEVES', 'POSIBLENG', 'MOULI', 'SA', 'PILIPINAS', 'KARONG', 'MAYO', '17', ',', 'MATUD', 'PA', 'NI', 'DOJ', 'SEC.', 'REMULLA', 'Posibleng', 'mouli', 'sa', 'Pilipinas', 'si', 'Thi... | [0, 1, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 5, 0, 5, 6, 0, 1, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 1, 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, 1, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0... | cebuaner |
4,076 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['2', 'KA', 'ESTUDYANTE', 'SA', 'TANJAY', ',', 'GITABANG', 'TUNGOD', 'SA', 'GRABENG', 'KAINIT', 'Duha', 'ka', 'mga', 'estudyante', 'sa', 'Tanjay', 'National', 'High', 'School', '(', 'Opao... | [0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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... | cebuaner |
4,077 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SENADOR', ',', 'GISUGYOT', 'NGA', 'MAHIMONG', 'REQUIRED', 'ANG', '2ND', 'BOOSTER', 'BATOK', 'COVID-19', 'Gisugyot', 'ni', 'Sen.', 'Francis', 'Tolentino', 'nga', 'himuong', 'required', '... | [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, 1, 0, 0, 1, 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, 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] | cebuaner |
4,078 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE-SIBULAN', 'AIRPORT', ',', 'IKA-15', 'SA', ''BUSIEST', 'AIRPORTS', ''', 'SA', 'PH', 'Nahimutang', 'ang', 'Dumaguete-Sibulan', 'Airport', 'sa', 'ika-15', 'nga', 'ranggo', 'sa', ... | [5, 6, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0] | cebuaner |
4,079 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DBM', ':', 'TRABAHANTE', 'SA', 'GOBYERNO', ',', 'MAKADAWAT', 'SA', 'ILANG', 'MIDYEAR', 'BONUS', 'SUGOD', 'SA', 'MAY', '15', 'Makadawat', 'sa', 'ilang', 'midyear', 'bonus', 'ang', 'mga',... | [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, 3, 4, 4, 4, 4, 4, 4, 4, 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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,080 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['FDA', ',', 'GI-BAN', 'ANG', 'PAGPASULOD', 'OG', ''PROCESSED', 'PORK', ''', 'GIKAN', 'SA', 'SINGAPORE', 'TUNGOD', 'SA', 'ASF', 'Gimando', 'sa', 'Food', 'and', 'Drug', 'Administration', '... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 7, 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, 5, 0, 0, 0, 3, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 0... | cebuaner |
4,081 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'swerte', 'nga', 'tigpusta', 'ang', 'nakadaog', 'sa', 'kapin', 'P225', 'milyon', 'nga', 'jackpot', 'prize', 'sa', 'Mega', 'Lotto', '6', '/', '45', 'sa', 'draw', 'niini', 'ni... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0] | cebuaner |
4,082 | 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', 'kalihokan', 'sa', 'Dumaguete', 'Triathlon', 'nga', 'apilan', 'sa', 'dul-an', '400', 'ka', 'triathletes', 'gikan', 'sa', 'tibuok', 'nasud.', 'Ipahigayon', 'k... | [0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,083 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KONGKRETONG', 'TAYTAYAN', 'SA', 'BATINGUEL-JUNOB', ',', 'SUGDAN', 'NA', 'PAGTUKOD', 'KARONG', 'BULANA', 'Sugdan', 'na', 'karong', 'bulana', 'ang', 'pagtukod', 'sa', 'usa', 'ka', 'kongkr... | [0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 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, 1, 2, 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... | cebuaner |
4,084 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['EL', 'NIÑO', ',', 'GIPANGANDAMAN', 'NA', 'SA', 'DUMAGUETE', 'CITY', 'Nagpahigayon', 'ang', 'dakbayan', 'sa', 'Dumaguete', 'og', 'massive', 'information', 'drive', 'aron', 'maandam', 'an... | [7, 8, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 3, 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, 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... | cebuaner |
4,085 | 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', 'BATA', ',', 'PATAY', 'HUMAN', 'NAKAKAON', 'OG', 'BAKI', ';', '4', 'KA', 'IGSUON', ',', 'NAOSPITAL', 'Patay', 'ang', 'usa', 'ka', '5', 'anyos', 'nga', 'batang', 'lal... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 6, 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... | cebuaner |
4,086 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'SA', 'AYUNGON', ',', 'PATAY', 'HUMAN', 'MADASMAGAN', 'OG', 'SAKYANAN', 'NGA', 'GIMANEHO', 'OG', 'PULIS', 'Patay', 'ang', 'usa', 'ka', 'lalaki', 'human', 'siya', 'nilabang', 's... | [0, 0, 0, 0, 0, 0, 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, 1, 2, 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, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,087 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SU', ',', 'MAGTANOM', 'OG', '500,000', 'KA', 'MANGROVE', 'TREES', 'SA', 'HABAGATANG', 'NEGOR', 'Nakig-partner', 'ang', 'Silliman', 'University', '(', 'SU', ')', 'sa', 'GCash', 'ug', 'Un... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 3, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 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] | cebuaner |
4,088 | 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', ''colorized', ''', 'nga', 'litrato', 'sa', 'mga', 'estudyante', 'sa', 'Negros', 'Oriental', 'Provincial', 'High', 'School', 'nga', 'naggama', 'og', 'mga', 'muwebles... | [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] | cebuaner |
4,089 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SENADO', ',', 'GIAWHAG', 'ANG', 'COMELEC', 'NGA', 'IPAUBOS', 'ANG', 'NEGOR', 'SA', 'KONTROL', 'NIINI', 'Giawhag', 'sa', 'usa', 'ka', 'panel', 'sa', 'Senado', 'ang', 'Commission', 'on', ... | [0, 0, 0, 0, 3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 3, 4, 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, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 2, 2, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0... | cebuaner |
4,090 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gibanabanang', 'moabot', 'ngadto', 'sa', 'kapin', 'P55', 'milyones', 'ang', 'danyos', 'sa', 'nahitabong', 'sunog', 'sa', 'usa', 'ka', 'bodega', 'sa', 'Barangay', 'Bantayan', ',', 'Dumag... | [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, 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] | cebuaner |
4,091 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['P1-M', 'CASH', 'GIFT', 'BILL', 'ALANG', 'SA', 'MGA', 'PINOY', 'CENTENARIAN', ',', 'APRUBADO', 'NA', 'SA', 'KAMARA', 'Amendaran', 'sa', 'House', 'Bill', '7535', 'ang', 'Centenarian', 'La... | [0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 3, 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, 7, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,092 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JACKPOT', 'SA', 'MEGA', 'LOTTO', '6', '/', '45', ',', 'GILAOMANG', 'MOABOT', 'SA', 'KAPIN', 'P200-M', 'Gilaomang', 'moabot', 'ngadto', 'sa', 'kapin', 'P200', 'milyones', 'ang', 'jackpot... | [0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 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, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0] | cebuaner |
4,093 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DUMAGUETE', 'CITY', 'POLICE', 'STATION', ',', 'GIILA', 'ISIP', 'TOP', 'POLICE', 'STATION', 'SA', 'NEGOR', 'Gihatagan', 'ang', 'Dumaguete', 'City', 'Police', 'Station', 'og', 'Certificat... | [3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 6, 6, 6, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,094 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Padayong', 'gipalong', 'karon', 'sa', 'kabumberohan', 'ang', 'sunog', 'nga', 'niulbo', 'sa', 'usa', 'ka', 'bodega', 'sa', 'Barangay', 'Bantayan', ',', 'Dumaguete', 'City.', 'Gikatahong'... | [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] | cebuaner |
4,095 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LAING', 'BIKTIMA', 'NGA', 'NASAMDAN', 'SA', 'PAMPLONA', 'MASSACRE', ',', 'NAMATAY', 'NIADTONG', 'WEEKEND', 'Nisaka', 'na', 'ngadto', 'sa', 'pulo', 'ang', 'mga', 'namatay', 'sa', 'Pamplo... | [0, 0, 0, 0, 0, 7, 8, 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, 7, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0... | cebuaner |
4,096 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sumala', 'pa', 'sa', 'gipagawas', 'nga', 'datos', 'sa', 'PAGASA', ',', 'niabot', 'ngadto', 'sa', '40°C', 'ang', 'heat', 'index', 'sa', 'Dumaguete', 'City', 'niadtong', 'Dominggo', ',', ... | [0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,097 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sunog', 'niulbo', 'sa', 'karaang', 'Provincial', 'Capitol', 'Building', 'sa', 'Siquijor', 'sa', 'lungsod', 'sa', 'Larena', 'karong', 'Domingo', ',', 'Mayo', '7', ',', '2023.', 'Sa', 'pa... | [0, 0, 0, 0, 5, 6, 6, 0, 5, 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] | cebuaner |
4,098 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['COVID-19', ',', 'DILI', 'NA', 'USA', 'KA', 'GLOBAL', 'HEALTH', 'EMERGENCY', 'MATUD', 'PA', 'SA', 'WHO', 'Human', 'ang', 'kapin', '3', 'ka', 'tuig', 'nga', 'nagkatap', 'kini', 'sa', 'kal... | [7, 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, 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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 3, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,099 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MOTORISTA', ',', 'PATAY', 'SA', 'USA', 'KA', 'ROAD', 'ACCIDENT', 'SA', 'TANJAY', 'CITY', 'Patay', 'ang', 'usa', 'ka', 'lalaki', 'human', 'sa', 'usa', 'ka', 'road', 'accident', 'sa', 'Ba... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 1, 2, 2, 0, 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... | cebuaner |
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