Unnamed: 0 int64 0 335k | question stringlengths 17 26.8k | answer stringlengths 1 7.13k | user_parent stringclasses 29
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4,300 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'talagsaong', 'kometa', 'nga', 'wala', 'makita', 'sa', '50,000', 'ka', 'tuig', 'ang', 'molabay', 'sa', 'Earth', ',', 'mao', 'kini', 'ang', '"', 'The', 'Green', 'Comet', '"',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 7, 8, 8, 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] | cebuaner |
4,301 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LIBOAN', 'KA', 'MGA', 'TAMBAN', ',', 'NAANOD', 'SA', 'BAYBAYON', 'SA', 'HINOBA-AN', 'Nidagsa', 'sa', 'baybayon', 'ang', 'mga', 'residente', 'sa', 'Purok', '5', 'Taliptipon', ',', 'Culip... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 0, 0, 0, 0] | cebuaner |
4,302 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SILLIMAN', 'UNIVERSITY', ',', 'GIILA', 'ISIP', 'NO.', '1', 'SCHOOL', 'SA', 'NURSING', 'EXAM', 'Nag-una', 'ang', 'Silliman', 'University', '(', 'SU', ')', 'sa', 'lista', 'sa', 'mga', 'na... | [3, 4, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 3, 4, 4, 4, 4, 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, 3, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 1, 2, 2, 0, 3, 4, 4, 4, 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, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0... | cebuaner |
4,303 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SALAGDOONG', 'BEACH', 'SA', 'SIQUIJOR', ',', 'ABLIHAN', 'NA', 'SA', 'PUBLIKO', 'HUMAN', 'ANG', 'DUL-AN', '3', 'KA', 'TUIG', 'Sa', 'pipila', 'ka', 'bulan', ',', 'abrihan', 'na', 'alang',... | [5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 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, 7, 0] | cebuaner |
4,304 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PULIS', ',', 'GIDUNGGAB', 'PATAY', 'SA', 'AMLAN', 'Patay', 'ang', 'usa', 'ka', 'pulis', 'human', 'kini', 'gidunggab', 'sa', 'Barangay', 'Silab', 'sa', 'lungsod', 'sa', 'Amlan', 'ganinan... | [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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0... | cebuaner |
4,305 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PCHC', ':', 'MGA', 'TSEKE', 'KINAHANGLANG', 'ADUNAY', 'FULL', 'NUMERIC', 'ISSUE', 'DATES', 'SUGOD', 'SA', 'MAYO', 'Nagpahinumdom', 'sa', 'publiko', 'ang', 'Philippine', 'Clearing', 'Hou... | [3, 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, 7, 8, 8, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,306 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GINABOT', 'SA', 'DUMAGUETE.', 'Dili', 'na', 'kinahanglan', 'pa', 'nga', 'mobiyahe', 'og', 'Cebu', 'aron', 'makatilaw', 'sa', 'lamian', 'nga', 'ginabot', ',', 'tungod', 'kay', 'kini', 'a... | [0, 0, 5, 0, 0, 0, 0, 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, 5, 6, 6, 6, 0, 5, 6, 0] | cebuaner |
4,307 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gitay-og', 'sa', 'usa', 'ka', 'magnitude', '3.2', 'nga', 'linog', 'ang', 'pipila', 'ka', 'lugar', 'sa', 'Negros', 'Oriental', 'pasado', 'alas-3', 'karong', 'Huwebes', 'sa', 'hapon', ','... | [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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,308 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['EKONOMIYA', 'SA', 'PILIPINAS', 'NISAKA', 'NGADTO', 'SA', '7.6', '%', 'NIADTONG', '2022', 'Paspas', 'nga', 'nisaka', 'ang', 'ekonomiya', 'sa', 'Pilipinas', 'nga', 'gipaabot', 'niadtong',... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,309 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Walay', 'klase', 'karon', 'sa', 'mga', 'mosunod', 'nga', 'lugar', 'sa', 'Negros', 'Oriental', 'karong', 'Huwebes', ',', 'Enero', '26', ',', '2023', ',', 'tungod', 'sa', 'pag-ulan', 'sa'... | [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 |
4,310 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PATAYNG', 'LAWAS', 'SA', 'LALAKI', ',', 'NAKIT-AN', 'SA', 'USA', 'KA', 'PAYAG', 'SA', 'DUMAGUETE', 'Usa', 'ka', 'patay', 'nga', 'lawas', 'ang', 'nakit-an', 'sa', 'Purok', 'Kanangkaan', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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] | cebuaner |
4,311 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['44', 'KA', 'MIYEMBRO', 'SA', 'SAF', ',', 'NAPATAY', 'SA', 'ENGKWENTRO', 'SA', 'MINDANAO', 'Karong', 'adlawa', 'niadtong', '2015', ',', 'nahitabo', 'ang', 'Mamasapano', 'massacre', 'diin... | [0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0] | cebuaner |
4,312 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['JOLLIBEE', 'BRANDS', ',', 'NALAKIP', 'SA', 'MGA', 'PINAKAPABORITONG', 'RESTAURANT', 'CHAINS', 'SA', 'U.S.', 'Nalakip', 'sa', 'lista', 'sa', 'America', ''s', 'Favorite', 'Restaurant', 'C... | [3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 5, 0, 5, 0, 5, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 3, 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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,313 | 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', 'JAN.', '23', 'Nagtanyag', 'ang', 'Cebu', 'Pacific', 'og', 'P88', 'nga', 'plite', 'hangtod', 'sa', 'Enero', '23', ... | [3, 4, 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, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 5, 0, 5, 0, 5, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 5, 0, 5, 6, 0, 5, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,314 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Unsa', 'man', 'ang', 'mahimong', 'kapalaran', 'sa', 'imong', 'love', 'life', 'karong', 'Year', 'of', 'the', 'Rabbit', '?', 'Single', 'pa', 'ba', 'gihapon', 'ka', '?', 'Magkauyab', 'na',... | [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, 7, 0, 0, 0] | cebuaner |
4,315 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['USA', 'KA', 'TALAGSAONG', 'GREEN', 'COMET', ',', 'MOLABAY', 'SA', 'EARTH', 'KARONG', 'FEB.', '1', 'Usa', 'ka', 'talagsaong', 'berde', 'nga', 'kometa', 'ang', 'molabay', 'sa', 'Earth', '... | [0, 0, 0, 7, 8, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,316 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PH', 'MO-IMPORT', 'OF', '450,000', 'MT', 'SA', 'KALAMAY', 'ALANG', 'SA', '2023', 'Nag-andam', 'na', 'ang', 'Sugar', 'Regulatory', 'Administration', '(', 'SRA', ')', 'aron', 'sa', 'pag-i... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 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... | cebuaner |
4,317 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PINAKAGULANG', 'NGA', 'TAWO', 'SA', 'KALIBUTAN', ',', 'NAMATAY', 'NA', 'SA', 'EDAD', 'NGA', '118', 'Namatay', 'na', 'ang', 'French', 'nga', 'madre', 'nga', 'si', 'Lucile', 'Randon', ','... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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, 5, 6, 6, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 5, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
4,318 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['AIRASIA', 'NAGTANYAG', 'OG', 'P71', 'NGA', 'PLITE', 'HANGTOD', 'SA', 'ENERO', '29', 'Nagtanyag', 'ang', 'AirAsia', 'og', 'seat', 'sale', 'nga', 'P71', 'hangtod', 'sa', 'Enero', '29', ',... | [3, 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, 5, 0, 0, 5, 0, 5, 0, 0, 5, 0, 0, 5, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 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, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0... | cebuaner |
4,319 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DOMESTIC', 'AIRLINES', 'PAUBSAN', 'ANG', 'PLITE', 'KARONG', 'PEBRERO', 'Gikompirmar', 'sa', 'domestic', 'airlines', 'nga', 'Philippine', 'Airlines', ',', 'Cebu', 'Pacific', 'ug', 'AirAs... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 3, 4, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,320 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BATAN-ON', ',', 'PATAY', 'HUMAN', 'NASUYOP', 'SA', 'TAMBURONG', 'SA', 'PAMPLONA', 'Usa', 'ka', 'batan-on', 'ang', 'namatay', 'human', 'nasuyop', 'sa', 'tamburong', 'ug', 'nalumos', 'sa'... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 3, 0, 5, 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... | cebuaner |
4,321 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PINASKUHAN', 'ALANG', 'SA', '34K', 'KA', 'SENIOR', 'CITIZEN', ',', 'PWD', ',', 'UG', 'PAMILYANG', 'KABUS', 'SA', 'DUMAGUETE', ',', 'I-APOD-APOD', 'KARONG', 'SEMANA', 'Iapod-apod', 'na',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,322 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PBBM', ':', 'PILIPINAS', 'KINAHANGLAN', 'NANG', 'MOANGKAT', 'OG', 'SIBUYAS', 'TUNGOD', 'KAY', 'KULANG', 'ANG', 'LOKAL', 'NGA', 'ANI', 'Gibutyag', 'ni', 'President', 'Ferdinand', 'Marcos... | [1, 0, 5, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,323 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAULANON', 'NGA', 'WEEKEND', ',', 'GILAOMAN', 'TUNGOD', 'SA', 'LPA', 'Magpadayon', 'ang', 'pag-ulan', 'sa', 'pipila', 'ka', 'parte', 'sa', 'nasud', 'karong', 'weekend', 'tungod', 'sa', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 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, 5, 6, 0, 5, 6, 0, 5, 6, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,324 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mga', 'hulagway', 'sa', 'usa', 'ka', 'batang', 'babayi', 'nga', 'nakakuha', 'sa', 'kasingkasing', 'sa', 'mga', 'netizens', 'diin', 'nag-costume', 'kini', 'og', 'Sto.', 'Niño', '.'] Use ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
4,325 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Bes', ',', 'kung', 'ikaw', 'ang', 'pangutan-on', ',', 'malas', 'ba', 'ang', '#', 'FridayThe13th', '?', 'Giingong', 'malas', 'ang', '13', 'tungod', 'nagsunod', 'kini', 'sa', 'number', '1... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
4,326 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Pipila', 'ka', 'tindahan', 'sa', 'Dao', 'Public', 'Market', 'sa', 'Tagbilaran', 'City', ',', 'Bohol', 'ang', 'nag-promo', 'pinaagi', 'sa', 'pagbayad', 'sa', 'GCash', ',', 'sama', 'sa', ... | [0, 0, 0, 0, 5, 6, 6, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,327 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Girampa', 'ni', 'Celeste', 'Cortesi', 'ang', 'iyang', 'national', 'costume', 'atol', 'sa', 'preliminary', 'competition', 'sa', '#', '71stMissUniverse', '.'] Use the following schema: 1 ... | [0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0] | cebuaner |
4,328 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BALAUDNON', 'PAGBALIK', 'SA', 'NEGROS', 'ISLAND', 'REGION', ',', 'GIAPRUBAHAN', 'NA', 'SA', 'USA', 'KA', 'PANEL', 'SA', 'KAMARA', 'Giaprobahan', 'sa', 'House', 'committee', 'sa', 'local... | [0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 3, 4, 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, 5, 0, 0, 0, 5, 6, 6, 6, 0, 1, 2, 0, 0, 0, 0, 0, 5, 0, 1, 2, 2, 0, 5, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 5, 6, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0... | cebuaner |
4,329 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Girampa', 'ni', 'Celeste', 'Cortesi', 'ang', 'iyang', 'evening', 'gown', 'atol', 'sa', 'preliminary', 'competition', 'sa', '#', '71stMissUniverse.', 'Si', 'Cortesi', 'ang', 'pambato', '... | [0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 0, 0, 0, 3, 0, 0, 0, 0] | cebuaner |
4,330 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['COVID-19', 'EMERGENCY', ',', 'POSIBLENG', 'MATAPOS', 'NA', 'KARONG', '2023', ',', 'MATUD', 'PA', 'SA', 'WHO', 'Gipanan-aw', 'sa', 'World', 'Health', 'Organization', '(', 'WHO', ')', 'an... | [7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 3, 4, 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, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,331 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['AMPING', 'GIHAPON', 'SA', 'ULAN', ',', 'BESHIE', '!', 'Giisa', 'sa', 'PAGASA', 'ang', 'ORANGE', 'RAINFALL', 'WARNING', 'sa', 'Negros', 'Oriental', 'ug', 'Siquijor', 'karong', 'adlawa', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,332 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Beshie', ',', 'ania', 'ang', 'mga', 'emergency', 'numbers', 'alang', 'sa', 'mga', 'lokal', 'nga', 'awtoridad', 'ning', 'dakbayan', 'sa', 'Dumaguete.', 'Karong', 'walay', 'hunong', 'ang'... | [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] | cebuaner |
4,333 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Suspendido', 'na', 'ang', 'klase', 'sa', 'tanang', 'lebel', 'sa', 'tanang', 'pampubliko', 'ug', 'pribadong', 'eskuwelahan', 'sa', 'tibuok', 'DUMAGUETE', 'CITY', 'karong', 'Huwebes', ','... | [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, 1, 2, 0, 0, 0, 0, 0] | cebuaner |
4,334 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gisuspinde', 'na', 'ang', 'klase', 'sa', 'tanang', 'lebel', 'sa', 'tanang', 'pampubliko', 'ug', 'pribadong', 'tunghaan', 'sa', 'tibuok', 'Negros', 'Oriental', 'karong', 'Huwebes', ',', ... | [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, 1, 2, 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] | cebuaner |
4,335 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DOBLE', 'AMPING', 'SA', 'ULAN', ',', 'BESHIE', '!', 'Giisa', 'na', 'sa', 'PAGASA', 'ang', 'kinatas-an', 'nga', 'RED', 'RAINFALL', 'WARNING', 'sa', 'Negros', 'Oriental', 'karong', 'gabii... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 5, 0, 0, 5, 0] | cebuaner |
4,336 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipaubos', 'na', 'sa', 'PAGASA', 'ang', 'tibuok', 'Negros', 'Oriental', 'sa', 'ORANGE', 'RAINFALL', 'WARNING', 'tungod', 'sa', 'epekto', 'sa', 'low-pressure', 'area', 'ug', 'shear', 'li... | [0, 0, 0, 3, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0] | cebuaner |
4,337 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SIDLAKAN', 'DANCE', 'COMPANY', 'SA', 'NEGOR', ',', 'MOSALMOT', 'SA', 'FIDAF', 'BRAZIL', 'WORLD', 'CHAMPIONSHIP', '2023', 'Ang', 'Sidlakan', 'Dance', 'Company', '(', 'SDC', ')', 'mao', '... | [3, 4, 4, 0, 5, 0, 0, 0, 7, 8, 8, 8, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 7, 8, 8, 8, 8, 0, 7, 8, 8, 8, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 5, 6, 0, 0, 0, 0, 0, 0, 5, 0, 0, 7, 8, 0, 5, 6, 0, 0, 0, 7, 8, 8... | cebuaner |
4,338 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Giisa', 'sa', 'PAGASA', 'ang', 'yellow', 'heavy', 'rainfall', 'warning', 'sa', 'mga', 'lalawigan', 'sa', 'Siquijor', 'ug', 'Negros', 'Oriental', ',', 'lakip', 'na', 'ang', 'Dumaguete', ... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,339 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LPA', ',', 'SHEAR', 'LINE', 'MAGDALA', 'OG', 'PAG-ULAN', 'SA', 'KABISAY-AN', 'Sa', 'mosunod', 'nga', '24', 'ka', 'oras', ',', 'magdala', 'ang', 'Low', 'Pressure', 'Area', '(', 'LPA', ')... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 6, 0, 5, 6, 6, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 5, 6, 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, 6, 6, 6, 6, 0, 0, 0, 0, 0... | cebuaner |
4,340 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gilugwayan', 'sa', 'Miss', 'Universe', 'Philippines', 'ang', 'deadline', 'sa', 'aplikasyon', 'alang', 'sa', 'maong', 'pageant', 'karong', '2023.', 'Gianunsyo', 'sa', 'organisasyon', 'ng... | [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, 3, 4, 4, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 5, 6, 6, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0... | cebuaner |
4,341 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LPA', 'MAGPAULAN', 'SA', 'NEGROS', 'ORIENTAL', 'UG', 'KABISAY-AN', 'Gibantayan', 'ang', 'usa', 'ka', 'low', 'pressure', 'area', '(', 'LPA', ')', 'nga', 'anaa', 'sa', '425', 'km', 'sa', ... | [0, 0, 0, 5, 6, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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, 5, 0, 5, 6, 0, 5, 6, 0, 5, 6, 6, 0, 5, 6, 6, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0... | cebuaner |
4,342 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['USA', 'KA', 'LANGYAW', ',', 'GIINGONG', 'GIATAKE', 'SA', 'LAING', '3', 'KA', 'MGA', 'LANGYAW', 'Usa', 'ka', 'langyaw', 'ang', 'giingong', 'giatake', 'sa', 'laing', 'tulo', 'ka', '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, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 7, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0... | cebuaner |
4,343 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Patay', 'ang', 'usa', 'ka', 'babaye', 'sa', 'lungsod', 'sa', 'Amlan', 'human', 'siya', 'gitigbas', 'og', 'makadaghan', 'samtang', 'naglakaw', 'sa', 'dalan', 'kagabii', ',', 'Enero', '9'... | [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, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 5, 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, 5, 0, 0, 0, 0, 0... | cebuaner |
4,344 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'pagsulod', 'sa', 'bag-ong', 'tuig', ',', 'aduna', 'sab', 'mga', 'bag-ong', 'pangalan', 'sa', 'mga', 'bagyo', 'nga', 'gikabalak-ang', 'mosulod', 'sa', 'nasud', 'karong', '2023', '.... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,345 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['TROUGH', 'SA', 'LPA', 'MAGDALA', 'OG', 'PAG-ULAN', 'SA', 'VISAYAS', ',', 'MINDANAO', 'Gilaoman', 'nga', 'magdala', 'og', 'pag-ulan', 'sa', 'pipila', 'ka', 'bahin', 'sa', 'Visayas', 'ug'... | [0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 5, 0, 5, 0, 5, 6, 0, 0, 0, 0, 0, 0, 5, 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] | cebuaner |
4,346 | 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', 'usa', 'ka', 'residential', 'area', 'dapit', 'sa', 'Jose', 'Pro', 'Teves', '(', 'Cervantes', ')', 'Street', ',', 'Barangay', '8', ',', 'Dumaguete', 'City', 'karo... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 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] | cebuaner |
4,347 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BES', ',', 'NANGITA', 'KA'G', 'TRABAHO', '?', 'Mao', 'kini', 'ang', 'mga', 'in-demand', 'nga', 'trabaho', 'nga', 'pwede', 'nimong', 'sudlan', 'sa', 'Pilipinas', '.'] Use the following s... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
4,348 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['2023', 'MAAYONG', 'TUIG', 'ALANG', 'SA', 'GUGMA', 'UG', 'PAGPANGANAK', ',', 'MATUD', 'SA', 'USA', 'KA', 'FENG', 'SHUI', 'EXPERT', 'Gibutyag', 'ni', 'Feng', 'Shui', 'master', 'Marites', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 7, 8, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 7, 8, 8, 8, 8, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 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, 0, 7, 0... | cebuaner |
4,349 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GRADUATE', 'SA', 'COSCA', ',', 'TOP', '5', 'SA', 'DECEMBER', '2022', 'RADTECH', 'BOARD', 'EXAM', 'Nalakip', 'si', 'Jose', 'Nico', 'Ramaila', 'Maicom', 'sa', 'mga', 'topnotchers', 'sa', ... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 1, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,350 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['INDIAN', 'RESTAURANT', 'SA', 'DGTE', ',', 'NAGSIRA', 'OG', '3', 'KA', 'ADLAW', 'TUNGOD', 'SA', 'KRISIS', 'SA', 'SIBUYAS', 'Tulo', 'ka', 'adlaw', 'nga', 'nagsira', 'ang', 'Roti', 'Boss',... | [7, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 5, 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] | cebuaner |
4,351 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['INFLATION', 'RATE', 'NISAKA', 'NGADTO', 'SA', '8.1', '%', 'NIADTONG', 'DISYEMBRE', '2022', 'Mas', 'paspas', 'nga', 'nisaka', 'ang', 'inflation', 'rate', 'sa', 'nasud', 'niadtong', 'Disy... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0... | cebuaner |
4,352 | 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', 'P1', 'NGA', 'PLITE', 'SA', 'LOCAL', ',', 'INT'L', 'FLIGHTS', 'Nagtanyag', 'ang', 'Cebu', 'Pacific', 'og', 'seat', 'sale', 'promos', 'gikan', 'Manil... | [3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 5, 0, 5, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 6, 0, 5, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,353 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'NGA', 'NAG-PROPOSE', 'SA', 'IYANG', 'GF', ',', 'NIHANGYO', 'NGA', 'BAYARAN', 'ANG', 'KATUNGA', 'SA', 'ENGAGEMENT', 'RING', 'Usa', 'ka', 'lalaki', 'sa', 'Taiwan', 'ang', 'nakak... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,354 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gi-share', 'sa', 'NASA', 'ang', 'usa', 'ka', 'hulagway', 'sa', 'Adlaw', ',', 'samtang', 'ni-transition', 'kita', 'ngadto', 'sa', '2023', 'nga', 'nagtimaan', 'sa', 'bag-ong', 'orbit', 's... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0] | cebuaner |
4,355 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Pipila', 'ka', 'BPI', 'users', 'ang', 'nagreklamo', 'nga', 'nakuhaan', 'kuno', 'ang', 'ilang', 'available', 'balance', 'pinaagi', 'sa', '"', '0431', 'Debit', 'Memo', '"', 'nga', 'nigawa... | [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, 7, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,356 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'pawikan', 'ang', 'napalgang', 'patay', 'sa', 'kabaybayunan', 'sa', 'Barangay', 'Tapon', 'Norte', 'B', 'sa', 'lungsod', 'sa', 'San', 'Jose', 'karong', 'hapon', '(', 'Jan.', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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] | cebuaner |
4,357 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['TRICYCLE', 'DRIVER', 'GIULI', 'ANG', 'NAKIT-ANG', 'WALLET', 'NGA', 'ADUNA'Y', 'KWARTA', ',', 'IMPORTANTENG', 'MGA', 'DOKUMENTO', 'Usa', 'ka', 'tricycle', 'driver', 'ang', 'nitahan', 'sa... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 6, 0, 5, 6, 0, 5, 6, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0... | cebuaner |
4,358 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Unang', 'adlaw', 'sa', '2023', 'apan', 'halos', 'walay', 'eroplano', 'nga', 'makitang', 'galupad', 'karon', 'bisan', 'asa', 'sa', 'Pilipinas', 'human', 'nga', 'gi-“hold”', 'ang', 'mga',... | [0, 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, 6, 6, 6, 6, 0, 0, 0, 0] | cebuaner |
4,359 | 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', 'ang', 'kanhing', 'Santo', 'Papa', 'nga', 'si', 'Pope', 'Benedict', 'XVI', 'karong', 'adlawa', ',', 'Dec.', '31', ',', '2022', ',', 'sa', '... | [0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 1, 2, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 7, 8, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0... | cebuaner |
4,360 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['GALLUP', 'YEAREND', 'SURVEY', ':', 'PH', 'PINAKAMALIPAYONG', 'NASUD', 'SA', 'TIBUOK', 'KALIBUTAN', 'SA', '2022', 'Ang', 'Pilipinas', 'mao', 'ang', 'pinakamalipayon', 'nga', 'nasud', 'sa... | [3, 0, 0, 0, 5, 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, 3, 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, 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, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,361 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['CONTRACTUAL', ',', 'JOB', 'ORDER', 'WORKERS', 'SA', 'DGTE', 'MAKADAWAT', 'OG', 'P3,000', 'ISIP', 'GRATUITY', 'PAY', 'Makadawat', 'og', 'P3,000', 'matag', 'usa', 'ang', 'mga', 'kwalipika... | [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, 5, 0, 0, 0, 0, 1, 2, 0, 0, 7, 8, 8, 8, 0, 3, 4, 4, 4, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,362 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SOLON', ':', 'DILI', 'ANGAY', 'MABALAKA', 'ANG', 'PUBLIKO', 'KUNG', 'DILI', 'DAYON', 'MAKAREHISTRO', 'SA', 'SIM', 'CARDS', 'Usa', 'ka', 'magbabalaod', 'ang', 'nipasalig', 'sa', 'publiko... | [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, 1, 2, 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, 7, 8, 8, 8, 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... | cebuaner |
4,363 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MAGTIAYON', 'NGA', 'ADUNAY', 'PAREHA', 'NGA', 'BIRTHDAY', ',', 'GI-WELCOME', 'ANG', 'ILANG', 'BABY', 'SA', 'ILANG', 'ADLAW', 'SAB', 'NGA', 'NATAWHAN', 'Usa', 'ka', 'magtiayon', 'nga', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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, 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 |
4,364 | 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', 'nipatad', 'ang', 'naka-jackpot', 'sa', 'kapin', 'P114', 'milyon', 'human', 'sa', 'pag-draw', 'sa', 'winning', 'combination', 'sa', 'Mega', 'Lotto', '6', '/... | [0, 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, 0] | cebuaner |
4,365 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LALAKI', 'NI-AMBAK', 'GIKAN', 'SA', 'GISAKYANG', 'BARKO', 'Usa', 'ka', 'lalaki', 'ang', 'ni-ambak', 'gikan', 'sa', 'gisakyang', 'barko', 'nga', 'paingon', 'unta', 'sa', 'Cagayan', 'de',... | [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, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,366 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BUGNAW', 'NGA', 'PANAHON', 'MASINATI', 'SA', 'PASKO', 'Magpadayon', 'ang', 'bugnaw', 'nga', 'hangin', 'dala', 'sa', 'kusog', 'nga', 'Northeast', 'Monsoon', 'o', 'Amihan', 'sa', 'dakong'... | [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, 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, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,367 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NEGOR', 'SWIMMING', 'TEAM', 'NAKADAOG', 'OG', '8', 'GOLD', 'MEDAL', ',', '2', 'BRONZE', 'MEDAL', 'SA', 'BATANG', 'PINOY', '2022', 'Nakadaog', 'ang', 'swimming', 'team', 'sa', 'Negros', ... | [3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 5, 6, 6, 6, 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, 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... | cebuaner |
4,368 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['14', 'BALOT', 'VENDORS', ',', 'NAKADAWAT', 'OG', 'STAINLESS', 'STEEL', 'CARTS', 'ISIP', 'SUPORTA', 'SA', 'ILANG', 'PANGINABUHIAN', 'Giapod-apod', 'ang', '14', 'ka', 'stainless', 'steel'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,369 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Walay', 'klase', 'ug', 'walay', 'trabaho', 'karong', 'Lunes', ',', 'Dec.', '26', ',', '2022', ',', 'subay', 'sa', 'proklamasyon', 'ni', 'Presidente', 'Ferdinand', 'Marcos', 'Jr.', 'Suma... | [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, 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, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,370 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['3', 'PATAY', 'SA', 'GITUOHANG', 'ROBBERY', 'WITH', 'HOMICIDE', 'SA', 'ZAMBOANGUITA', 'Tulo', 'ang', 'patay', 'sa', 'gituohang', 'Robbery', 'with', 'Homicide', 'sa', 'Sitio', 'Cambilo', ... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,371 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BALAUDON', 'NGA', 'NAGTINGUHA', 'SA', 'FREE', 'TUITION', 'ALANG', 'SA', 'LAW', 'STUDENTS', ',', 'GIDUSO', 'Gipasaka', 'ni', 'Senator', 'Raffy', 'Tulfo', 'ang', 'usa', 'ka', 'balaudnon',... | [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, 1, 0, 7, 8, 8, 8, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,372 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LGU-DUMAGUETE', 'MOHATAG', 'OG', 'P3,000', 'NGA', 'HONORARIA', 'ALANG', 'SA', 'PUBLIC', 'SCHOOL', 'TEACHERS', 'Giaprobahan', 'ni', 'Mayor', 'Felipe', 'Remollo', 'ang', 'paghatag', 'og',... | [3, 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, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 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, 0, 0, 0, 0, 0, 0, 0, 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 |
4,373 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['REGULAR', ',', 'CASUAL', 'EMPLOYEES', 'SA', 'CITY', 'GOV'T', 'MAKADAWAT', 'OG', 'P15,000', 'MATAG', 'USA', ';', 'JOB', 'ORDER', 'WORKERS', 'MAKADAWAT', 'SAB', 'OG', 'RICE', 'SUBSIDY', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 1, 2, 0, 0, 7, 8, 8, 8, 0, 7, 0, 0, 0, 0, 1, 2, 2, 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... | cebuaner |
4,374 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LGU-DUMAGUETE', 'MOHATAG', 'OG', 'P3,000', 'NGA', 'HONORARIA', 'ALANG', 'SA', 'PUBLIC', 'SCHOOL', 'TEACHERS', 'Giaprobahan', 'ni', 'Mayor', 'Felipe', 'Remollo', 'ang', 'paghatag', 'og',... | [3, 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, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 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, 0, 0, 0, 0, 0, 0, 0, 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 |
4,375 | 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', 'NGC', '6956', ',', 'usa', 'ka', '"', 'spiral', 'galaxy', 'of', 'bright', 'blue', 'swirls.', '"', 'Nahimutang', 'kini', 'sa', 'gilay-on', 'nga', '214', 'million', '... | [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, 7, 0] | cebuaner |
4,376 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Subay', 'sa', 'bag-ong', 'balaod', 'nga', 'SIM', 'Registration', 'Act', '(', 'SRA', ')', ',', 'kinahanglan', 'nga', 'iparehistro', 'ang', 'gipanag-iyang', 'SIM', 'sugod', 'karong', 'Dis... | [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] | cebuaner |
4,377 | 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', 'ALANG', 'SA', 'DOMESTIC', 'DESTINATIONS', 'Nagtanyag', 'ang', 'Cebu', 'Pacific', 'og', 'one-way', 'base', 'fare', 'nga', 'in... | [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, 0, 0, 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 |
4,378 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ang', 'Negros', 'Oriental', 'State', 'University', '(', 'NORSU', ')', '-', 'Dumaguete', 'sa', 'mga', 'nanguna', 'nga', 'tunghaan', 'sa', 'nasud', 'nga', 'aduna'y', 'dako', 'nga',... | [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, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,379 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'migradwar', 'sa', 'Silliman', 'University', 'ang', 'nalakip', 'sa', 'Top', '9', 'sa', '2022', 'Licensure', 'Examination', 'for', 'Teachers', '(', 'LET', ')', '.', 'Nakakuha... | [0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 0, 1, 2, 2, 2, 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] | cebuaner |
4,380 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BAGYONG', 'ODETTE', 'NAGBILIN', 'OG', 'KADAOT', 'SA', 'NEGROS', 'ORIENTAL', 'Karong', 'adlawa', 'niadtong', '2021', ',', 'nagbilin', 'og', 'dakong', 'kadaot', 'ang', 'Bagyong', 'Odette'... | [7, 8, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 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, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,381 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NTC', 'NAGPASIDAAN', 'NA', 'SAB', 'SA', 'MGA', 'BAG-ONG', 'SCHEMES', 'SA', 'TEXT', 'SCAMS', 'Nagpasidaan', 'ang', 'National', 'Telecommunications', 'Commission', '(', 'NTC', ')', 'sa', ... | [3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,382 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SIM', 'CARD', 'REGISTRATION', ',', 'IPATUMAN', 'KARONG', 'DISYEMBRE', '27', 'Nangandam', 'na', 'ang', 'mga', 'kompanya', 'sa', 'telecommunications', 'sa', 'pagsugod', 'sa', 'ilang', 'ta... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,383 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sigurado', 'nga', 'malipayon', 'gyud', 'ang', 'imong', 'Pasko', 'kung', 'ikaw', 'ang', 'mosunod', 'nga', 'mahimong', 'milyonaryo', '!', 'Wala', 'pa', 'gihapon', 'nakadaog', 'sa', 'kapin... | [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, 8, 8, 8, 8, 0] | cebuaner |
4,384 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BORACAY', 'DELIKADO', 'NGA', 'MAHUGNO', 'TUNGOD', 'SA', 'NAKIT-AN', 'NGA', '815', 'KA', 'SINKHOLES', 'Nipasidaan', 'ang', 'Department', 'of', 'Environment', 'and', 'Natural', 'Resources... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,385 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['US', 'RESEARCHERS', 'GIANUNSYO', 'ANG', 'MAKASAYSAYANONG', 'KALAMPUSAN', 'SA', 'NUCLEAR', 'FUSION', 'Gianunsyo', 'sa', 'mga', 'US', 'researchers', 'ang', 'makasaysayanong', 'kalampusan'... | [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,386 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nakuha', 'sa', 'NASA', 'ang', 'usa', 'ka', ''colorful', ''', 'nga', 'hulagway', 'nga', 'resulta', 'sa', 'supernova', 'explosion', 'sa', 'usa', 'ka', 'dakong', 'bituon', '.'] Use the fol... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,387 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nakadawat', 'og', 'cash', 'incentives', 'gikan', 'sa', 'Silliman', 'University', 'ang', 'mga', 'top-notchers', 'nga', 'sila', 'si', 'Angela', 'Claire', 'N.', 'Kitane', 'ug', 'Amari', 'J... | [0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 1, 2, 2, 2, 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, 1, 2, 2, 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, 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... | cebuaner |
4,388 | 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', 'P12', 'NGA', 'PLITE', 'HANGTOD', 'DISYEMBRE', '14', 'Nagtanyag', 'ang', 'Cebu', 'Pacific', 'og', 'P12', 'nga', 'plite', 'alang', 'sa', 'mga', 'biya... | [3, 4, 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, 5, 0, 0, 5, 0, 5, 0, 5, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 0, 5, 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, 0, 0, 0, 0, 0, 0... | cebuaner |
4,389 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'swerteng', 'nipatad', 'ang', 'nakadaog', 'sa', 'jackpot', 'nga', 'mobalor', 'og', 'kapin', 'P23', 'milyon', 'human', 'na-draw', 'ang', 'winning', 'combination', 'sa', 'Supe... | [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, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,390 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mga', 'hulagway', 'sa', 'Christmas', 'decorations', 'sa', 'Department', 'of', 'Public', 'Works', 'and', 'Highways', '(', 'DPWH', ')', '-', '2nd', 'District', 'sa', 'Cangmating', ',', 'S... | [0, 0, 0, 7, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,391 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mga', 'Dumagueteño', ',', 'nagtigom', 'na', 'karon', 'sa', 'Perdices', 'Coliseum', '(', 'Oval', ')', 'ning', 'dakbayan', 'karong', 'adlawa', 'alang', 'sa', '#', 'TMFunPasko', 'party.', ... | [0, 7, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 4, 0, 1, 2, 0, 1, 2, 0, 3, 0, 3, 0, 0, 0, 0, 0] | cebuaner |
4,392 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagpamatuod', 'nga', 'smash', 'hit', 'ang', 'anime', 'film', 'nga', '#', 'TheFirstSlamDunk', 'diin', 'nakakuha', 'kini', 'og', 'second', 'highest', 'first', 'day', 'gross', 'sa', 'Japan... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
4,393 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['80', 'KA', 'SAKAYAN', 'SA', 'PANGISDA', ',', 'GIAPOD-APOD', 'ALANG', 'SA', '240', 'KA', 'MGA', 'LOKAL', 'NGA', 'MANGINGISDA', 'Giapod-apod', 'ang', '80', 'ka', 'fiberglass', 'motorized'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 5, 6, 0, 5, 0, 5, 6, 6, 6, 6, 6, 6, 0, 5, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,394 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gihaya', 'na', 'karon', 'ang', 'patayng', 'lawas', 'sa', 'inilang', 'singer', 'nga', 'si', 'Jovit', 'Baldivino', 'sa', 'iyang', 'panimalay', 'sa', 'Rosario', ',', 'Batangas.', 'Nitaliwa... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 5, 6, 6, 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] | cebuaner |
4,395 | 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', 'ang', 'inilang', 'singer', 'nga', 'si', 'Jovit', 'Baldivino', 'karong', 'adlawa', ',', 'Dec.', '9', ',', '2022', ',', 'matud', 'pa', 'sa',... | [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, 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, 5, 0, 0, 0, 0, 3, 4, 4, 0, 3, 0, 0, 0] | cebuaner |
4,396 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['ASTRONAUT', 'FOOD', ''', 'O', 'FOOD', 'PILL', 'ALANG', 'SA', 'MGA', 'KABUS', ',', 'NAHISGUTAN', 'SA', 'CONFIRMATION', 'HEARING', 'SA', 'DOST', 'CHIEF', 'Nisantop', 'sa', 'hunahuna', 'sa... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 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, 7, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,397 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['NEGROS', 'ORIENTAL', 'UG', 'KABISAY-AN', 'MAKASINATI', 'OG', 'PAG-ULAN', 'TUNGOD', 'SA', 'TROUGH', 'SA', 'LPA', 'Nipagawas', 'og', 'Regional', 'Weather', 'Forecast', 'ang', 'PAGASA', 'V... | [5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 3, 4, 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, 5, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,398 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nag-andam', 'na', 'alang', 'sa', '#', 'TMFunPasko', 'karong', 'December', '10', ',', '3:00pm', ',', 'sa', 'Perdices', 'Coliseum', '(', 'Oval', ')', ',', 'Kagawasan', 'Freedom', 'Park', ... | [0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 1, 2, 0, 1, 2, 0, 3, 0, 3, 4, 0, 3, 0, 1, 0, 1, 2, 0, 1, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0] | cebuaner |
4,399 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nakakuha', 'og', 'atensyon', 'ang', ''unique', ''', 'nga', 'Christmas', 'tree', 'sa', 'Tagoloan', 'Municipal', 'Police', 'Station', 'sa', 'Tagoloan', ',', 'Misamis', 'Oriental', 'nga', ... | [0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 7, 8, 8, 8, 0, 5, 6, 6, 6, 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 |
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