Unnamed: 0 int64 0 335k | question stringlengths 17 26.8k | answer stringlengths 1 7.13k | user_parent stringclasses 29
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5,000 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Presidente', 'Ferdinand', '"', 'Bongbong', '"', 'Marcos', 'Jr.', 'sa', 'Domingo', 'ngadto', 'sa', 'mga', 'Pilipino', 'nga', 'mahimong', '"', 'conveyors', 'of', 'truth', '"', 'ug',... | [0, 0, 1, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,001 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipahibawo', 'sa', 'Cebu', 'Cordova', 'Link', 'Expressway', 'Corp', '(', 'CCLEC', ')', 'karong', 'Biyernes', ',', 'Marso', '31', ',', 'nga', 'nahuman', 'na', 'niini', 'ang', 'P60', 'mil... | [0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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... | cebuaner |
5,002 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Base', 'sa', 'pinakaulahing', 'report', 'sa', 'HIV', '/', 'Aids', 'Registry', 'of', 'the', 'Philippines', ',', 'adunay', '1,292', 'ka', 'bag-ong', 'kaso', 'sa', 'HIV', 'ang', 'gitaho', ... | [0, 0, 0, 0, 0, 3, 4, 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, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,003 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Misaad', 'si', 'Presidente', 'Ferdinand', 'Marcos', 'Jr.', 'nga', 'ang', 'iyang', 'administrasyon', 'magpadayon', 'sa', 'pagpangita', 'og', 'mga', 'solusyon', 'aron', 'mapalambo', 'pa',... | [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] | cebuaner |
5,004 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Naguol', 'si', 'Sen.', 'Robinhood', 'Padilla', ',', 'chairman', 'sa', 'Senate', 'Committee', 'on', 'Constitutional', 'Amendments', 'and', 'Revision', 'of', 'Codes', ',', 'nga', 'sa', '2... | [0, 0, 0, 1, 2, 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, 1, 2, 2, 0, 1, 2, 0, 0, 1, 2, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,005 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Kining', 'diskwento', 'sa', 'presyo', 'sa', 'liquefied', 'petroleum', 'gas', '(', 'LPG', ')', 'katumbas', 'sa', 'P100.98', 'ngadto', 'sa', 'P101.20', 'sa', 'halin', 'sa', '11-kg.', 'tan... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 7, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0] | cebuaner |
5,006 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ako', 'diay', 'si', 'kuan', 'dili', 'ko', 'sugtan', 'mag', 'uyab', 'pero', 'paminyo'on', 'ko'g', 'americano.', '#', 'PilipinasToday', '#', 'Bench', '#', 'KathrynBernardo'] Use the follo... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0] | cebuaner |
5,007 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Naay', 'nilabay', 'nga', 'wakwak', 'gabie', 'ba', ',', 'akong', 'gisinggitan', ''sana', 'all', 'palaagon', 'og', 'gabie'] 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] | cebuaner |
5,008 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Unsa', 'ang', 'imong', 'panaad', 'matag', 'Semana', 'Santa', '?'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a tourism-relate... | [0, 0, 0, 0, 0, 7, 8, 0] | cebuaner |
5,009 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Lisod', 'man', 'gani', 'touhan', 'ang', ''on', 'the', 'way', ''', 'kana', 'pa', 'kahang', ''i', 'will', 'stay', ''', '.'] 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, 0] | cebuaner |
5,010 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Wa', 'koy', 'labot', 'sa', 'April', 'Fools', ''', 'Day.', 'Adlaw-adlaw', 'man', 'pud', 'ko', 'giilad', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2... | [0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0] | cebuaner |
5,011 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Malipayong', 'gipaambit', 'sa', 'Fil-Am', 'Hollywood', 'actress', 'nga', 'si', 'Vanessa', 'Hudgens', 'ang', 'iyang', 'kasinatian', 'samtang', 'nagsuroysuroy', 'sa', 'Pilipinas.', 'Namat... | [0, 0, 0, 7, 5, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,012 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SANA', 'ALL', '!', 'Para', 'adunay', 'igong', 'panahon', 'ang', 'mga', 'kawani', 'sa', 'gobyerno', 'sa', 'pagbiyahe', 'sa', 'lainlaing', 'rehiyon', 'sa', 'nasud', 'tungod', 'kay', 'una'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
5,013 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Trending', 'karon', 'sa', 'Twitter', 'ang', 'appointment', 'sa', 'Fil-Am', 'Hollywood', 'actress', 'nga', 'si', 'Vanessa', 'Hudgens', 'isip', 'Global', 'Tourism', 'Ambassador', 'of', 't... | [0, 0, 0, 7, 0, 0, 0, 7, 5, 0, 0, 0, 1, 2, 0, 7, 8, 8, 8, 8, 8, 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, 5, 1, 2, 0, 0, 0, 0, 0] | cebuaner |
5,014 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Andam', 'na', 'ang', 'Mactan-Cebu', 'International', 'Airport', 'sa', 'pagdagsa', 'sa', 'mga', 'pasahero', 'nga', 'mobiyahe', 'alang', 'sa', 'Semana', 'Santa', ',', 'nga', 'magsugod', '... | [0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0] | cebuaner |
5,015 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'tigpamaba', 'sa', 'Partido', 'ng', 'Manggagawa', '(', 'PM', ')', '-Cebu', 'nga', 'si', 'Dennis', 'Derige', 'niingon', 'sa', 'SunStar', 'Cebu', 'karong', 'Biyernes', ',', 'Marso',... | [0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 1, 2, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,016 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Layo', 'sa', 'naandan', 'nga', 'hitsura', 'sa', 'batang', 'lalaki', 'ug', 'babaye', 'sa', 'eskuylahan', 'sa', 'iyang', 'mga', 'POV', 'vids', 'sa', 'TikTok', ',', 'ang', 'content', 'crea... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,017 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Murag', 'na', 'april', 'fools', 'man', 'ko', 'ani', 'ba', ',', 'hali', 'man', 'ning', 'John', 'Wick', 'akong', 'nakitan', '.'] Use the following schema: 1 = B-WIS: Beginning of a touris... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0] | cebuaner |
5,018 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Unsay', 'prank', 'na', 'gihimo', 'sa', 'imo', 'nga', 'dili', 'nimo', 'malimtan', '?'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,019 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Unsa', 'ang', 'imong', 'panaad', 'sa', ''Semana', 'Santa', '?'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a tourism-related ... | [0, 0, 0, 0, 0, 7, 8, 0] | cebuaner |
5,020 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ingna', 'imong', 'friend', 'nga', 'kusog', 'sa', 'unli', 'rice', ':', ''Testingan', 'nato', 'bi', 'kung', 'gasipa', 'na', 'ning', 'bata', '.', '''] Use the following schema: 1 = B-WIS: ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,021 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mahilom', 'ug', 'yano', 'ang', 'paghandum', 'ni', 'Presidente', 'Bongbong', 'Marcos', 'sa', 'Semana', 'Santa', ',', 'matod', 'niya', 'sa', 'dihang', 'nahinabi', 'sa', 'pagbukas', 'sa', ... | [0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 1, 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, 1, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 7, 0] | cebuaner |
5,022 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'pinakaulahing', 'Facebook', 'post', 'ni', 'Senador', 'Sonny', 'Angara', 'karong', 'Biyernes', ',', 'Marso', '31', ',', 'iyang', 'giingon', 'nga', 'ang', 'mga', 'Pilipino', 'kinaha... | [0, 0, 7, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 7, 8, 0, 0, 0, 0, 0, 0, 7, 0, 0, 5, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,023 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PALIHOG', 'BAYAD', 'NA', ''', 'LOOK', ':', 'Listahan', 'sang', 'utang', 'nga', 'naga', 'lab-ot', 'linibo', 'sa', 'isa', 'ka', 'tyangge', 'nga', 'nahamtang', 'sa', 'Talisay', ',', 'Negro... | [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, 0, 0, 0, 0] | cebuaner |
5,024 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'interbyu', 'sa', 'TV', 'host', 'nga', 'si', 'Kim', 'Atienza', 'sa', ''Fast', 'Talk', 'with', 'Boy', 'Abunda', ',', ''', 'masaligon', 'nga', 'niingon', 'si', 'Kim', 'nga', 'segurad... | [0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
5,025 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Usa', 'ka', 'pampasaherong', 'bus', 'sa', 'Rural', 'Transit', 'Mindanao', 'ang', 'nabangga', 'sa', 'usa', 'ka', 'cargo', 'truck', 'nga', 'gikargahan', 'og', 'isda', 'mga', 'alas', '3:00... | [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, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 0] | cebuaner |
5,026 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Donald', 'Trump', 'ang', 'unang', 'kanhi', 'presidente', 'sa', 'Estados', 'Unidos', 'nga', 'gipasakaan', 'og', 'kasong', 'kriminal', 'human', 'ang', 'grand', 'jury', 'sa', 'New', ... | [0, 1, 2, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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] | cebuaner |
5,027 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Matud', 'pa', 'ni', 'Lt.', 'Col.', 'Ardioleto', 'Cabagnot', ',', 'hepe', 'sa', 'Carcar', 'City', 'Police', ',', 'sa', 'pakighinabi', 'sa', 'SunStar', 'Cebu', ',', 'nagkanayon', 'nga', '... | [0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 4, 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, 5, 6, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,028 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Miabot', 'na', 'sa', 'P1,100,000', 'ang', 'reward', 'sa', 'bisan', 'kinsa', 'nga', 'makatabang', 'pagsulbad', 'sa', 'pagpatay', 'kang', 'Reyna', 'Leanne', 'Daguinsin', ',', 'ang', '22-a... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 0, 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 |
5,029 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'singer-songwriter', 'nga', 'si', 'Moira', 'Dela', 'Torre', 'nag-tweet', 'sa', 'iyang', 'Twitter', 'niadtong', 'Marso', '29.', 'Gikatakdang', 'ipagawas', 'ni', 'Moira', 'ang', 'iy... | [0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,030 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Kini', 'ang', 'isog', 'nga', 'pamahayag', 'ni', 'Sen.', 'Robinhood', 'Padilla', 'kon', 'dakpon', 'sa', 'International', 'Criminal', 'Court', '(', 'ICC', ')', 'ang', 'iyang', 'kaubang', ... | [0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 1, 2, 0] | cebuaner |
5,031 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Makita', 'sa', 'CCTV', 'footage', 'ang', 'lalaki', 'nga', 'suspek', 'nga', 'misaka', 'sa', 'rooftop', 'sa', 'usa', 'ka', 'establisemento', 'aron', 'makaabot', 'sa', 'dormitoryo', '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, 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, 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, 0, 0, 0, 0, 0, 0, 0, 5, 0... | cebuaner |
5,032 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Matud', 'pa', 'ni', 'Sen.', 'Ronald', ''Bato', ''', 'Dela', 'Rosa', 'niingon', 'nga', 'si', 'Presidente', 'Bongbong', 'Marcos', 'misaad', 'kaniya', 'nga', 'magpabilin', 'siyang', 'luwas... | [0, 0, 0, 0, 1, 2, 2, 2, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 1, 2, 0] | cebuaner |
5,033 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sorry', 'mao', 'ra', 'ni', 'amoang', 'kasilyas', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a tourism-related entity; 3 ... | [0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,034 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gi-flexible', 'sa', 'aktres', 'nga', 'si', 'AJ', 'Raval', 'ang', 'iyang', 'hulagway', 'samtang', 'gipakita', 'nga', 'natangtang', 'na', 'ang', 'iyang', 'breast', 'implants', '.'] Use th... | [0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,035 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'House', 'Speaker', 'Martin', 'Romuladez', 'maoy', 'temporaryong', 'mohulip', 'kang', 'Negros', 'Oriental', '3rd', 'District', 'Rep.', 'Arnolfo', 'Teves', 'Jr.', ',', 'kinsa', 'gih... | [0, 0, 0, 1, 2, 0, 0, 0, 0, 3, 4, 4, 4, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 1, 2, 0, 0, 0, 0] | cebuaner |
5,036 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Daghan', 'sa', 'mga', 'naluwas', 'ug', 'naluwas', 'ang', 'niambak', 'sa', 'dagat', 'human', 'nataranta', 'samtang', 'nagdilaab', 'ang', 'barko', 'ug', 'sa', 'dagat', 'naluwas', 'sila', ... | [0, 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, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 2, 0] | cebuaner |
5,037 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Pope', 'Francis', 'gidala', 'sa', 'Gemelli', 'hospital', 'sa', 'Roma', 'human', 'nagreklamo', 'sa', 'kalisud', 'sa', 'pagginhawa', 'sa', 'miaging', 'mga', 'adlaw.', 'Base', 'sa', ... | [0, 0, 1, 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, 7, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
5,038 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['ALAGANG', 'ANGARA', 'Nag-tweet', 'nitong', 'Miyerkules', ',', 'Marso', '29', ',', 'si', 'Pamilya', ',', 'Pasyente', 'at', 'Persons', 'with', 'Disabilities', '(', 'P3WD', ')', 'Party-lis... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 7, 8, 0] | cebuaner |
5,039 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Reyna', 'Leanne', 'Daguinsin', ',', '24', ',', 'lumad', 'nga', 'taga', 'Pila', ',', 'Laguna', ',', 'graduating', 'computer', 'science', 'student', 'sa', 'De', 'La', 'Salle', 'Univ... | [0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 3, 4, 4, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,040 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipaambit', 'sa', 'Filipina-American', 'actress', 'nga', 'si', 'Vanessa', 'Hudgens', 'ang', 'pipila', 'ka', 'mga', 'hulagway', 'sa', 'iyang', 'biyahe', 'sa', 'El', 'Nido', ',', 'Palawan... | [0, 0, 7, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0] | cebuaner |
5,041 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gibasol', 'ni', 'Senador', 'Ramon', ''Bong', ''', 'Revilla', 'Jr', 'Siya', 'adunay', 'mga', 'bato', 'sa', 'iyang', 'apdo', 'tungod', 'sa', 'pagkaon', 'sa', 'mga', 'chicharong', 'bulakla... | [0, 0, 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] | cebuaner |
5,042 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'dili', 'pa', 'modagsa', 'ang', 'mga', 'magpapanaw', 'atol', 'sa', 'Semana', 'Santa', ',', 'ang', 'Police', 'Regional', 'Office', '(', 'PRO', ')', '-Central', 'Visayas', 'mopakatap... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 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, 1, 2, 2, 0, 3, 4, 4, 4, 4, 4, 4, 4] | cebuaner |
5,043 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'pamilya', 'ni', 'Darlene', 'Uy', 'nitanyag', 'og', 'P50,000.00', 'nga', 'reward', 'money', 'kang', 'bisan', 'kinsa', 'nga', 'makatudlo', 'sa', 'iyang', 'nahimutangan', ',', 'ug',... | [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, 5, 6, 6, 0, 0, 0, 0, 0] | cebuaner |
5,044 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Taas', 'kuno'g', 'standards', ',', 'pero', 'nihilak', 'sa', 'ka-talking', 'stage', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuati... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,045 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Morag', 'curious', 'sila', 'si', 'Miss', 'Globe', '2003', 'ug', 'Miss', 'Earth', '2015', 'Priscilla', 'Meirelles', 'ug', 'bana', 'sa', 'aktor', 'nga', 'si', 'John', 'Estrada', 'tungod',... | [0, 0, 0, 0, 3, 4, 0, 0, 3, 4, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 2, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
5,046 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipahalipayan', 'ni', 'Presidente', 'Ferdinand', 'Marcos', ',', 'Jr', 'karong', 'Martes', 'ang', 'iyang', 'gisundan', ',', 'si', 'kanhi', 'Presidente', 'Rodrigo', 'Duterte', ',', 'sa', ... | [0, 0, 0, 1, 2, 2, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,047 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Matud', 'pa', 'ni', 'Alden', 'Richards', 'nga', 'dili', 'kini', 'ang', 'una', 'niyang', 'kasinatian', 'sa', 'scuba', 'diving', 'apan', 'kini', 'ang', 'unang', 'higayon', 'nga', 'nanguha... | [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] | cebuaner |
5,048 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Matud', 'pa', 'ni', 'Capt.', 'Ar-jay', 'Dangarang', ',', 'hepe', 'sa', 'Isabela', 'Municipal', 'Police', ',', 'nga', 'wala', 'pa', 'nila', 'matino', 'ang', 'pagkatawo', 'sa', 'mga', 'bi... | [0, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 4, 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] | cebuaner |
5,049 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['matod', 'ni', 'DepEd', 'spokesperson', 'Michael', 'Poa.', 'dugang', 'pa', 'nya.', 'Karong', 'Martes', ',', 'Marso', '28', ',', 'si', 'Senador', 'Sherwin', 'Gatchalian', ',', 'chairman',... | [0, 0, 3, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 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, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,050 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'uga', 'ug', 'init', 'nga', 'panahon', 'mahimong', 'hinungdan', 'sa', 'pagkunhod', 'sa', 'suplay', 'sa', 'tubig', 'sa', 'Cebu', ',', 'matod', 'sa', 'meteorologist', 'sa', 'estado'... | [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, 7, 8, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 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... | cebuaner |
5,051 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Tungod', 'sa', 'grabeng', 'hulga', 'sa', 'iyang', 'kinabuhi', ',', 'ingon', 'man', 'sa', 'iyang', 'pamilya', ',', 'kini', 'gikompirmar', 'karong', 'Martes', ',', 'Marso', '28', ',', 'ni... | [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, 5, 6, 6, 6, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,052 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'ka', 'video', 'sa', 'aktuwal', 'nga', 'pagluwas', 'sa', 'siyam', 'ka', 'Congolese', 'nga', 'mga', 'minero', 'nga', 'natanggong', 'gikan', 'sa', 'usa', 'ka', 'nahugno', 'nga', 'min... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,053 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipaambit', 'sa', 'aktres', 'nga', 'si', 'Vanessa', 'Hudgens', 'ang', 'mga', 'eksena', 'gikan', 'sa', 'iyang', 'paglakaw', 'sa', 'kaadlawon', 'sa', 'Palawan', '.'] Use the following sch... | [0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
5,054 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'David', 'LIcauco', 'hapit', 'na', 'moundang', 'sa', 'showbiz', 'aron', 'motutok', 'sa', 'iyang', 'mga', 'negosyo', 'sa', 'wala', 'pa', 'siya', 'gianggaan', 'og', 'Sa', 'vlog', 'sa... | [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, 2, 0, 0, 0, 1, 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] | cebuaner |
5,055 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Wala', 'bay', ''Gibiyaan', ''', 'dira', 'para', 'maka-relate', 'ra', 'pud', 'ko', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuatio... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,056 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['PARI', 'PAJUD', ',', 'MOHIMO', 'OG', 'INAGANI', '(', 'sad', ')', 'Subay', 'sa', 'warrant', 'of', 'arrest', 'nga', 'giluwatan', 'ni', 'Sagay', 'Regional', 'Trial', 'Court', 'Judge', 'Reg... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 5, 6, 0, 5, 6, 6, 0, 0, 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] | cebuaner |
5,057 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Wa', 'nay', 'sunod', 'nga', 'himuon', 'ang', 'gobyerno', 'human', 'gibasura', 'sa', 'International', 'Criminal', 'Court', '(', 'ICC', ')', 'ang', 'hangyo', 'niini', 'nga', 'suspensuhon'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 5, 0, 0, 0, 5, 0] | cebuaner |
5,058 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'heat', 'index', 'sa', 'Manila', 'anaa', 'sa', '33', 'degrees', 'Celsius', 'sumala', 'sa', 'website', 'sa', 'Weather', 'Atlas', '.'] Use the following schema: 1 = B-WIS: Beginning... | [0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0] | cebuaner |
5,059 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Tungod', 'sa', 'grabeng', 'hulga', 'sa', 'iyang', 'kinabuhi', ',', 'ingon', 'man', 'sa', 'iyang', 'pamilya', ',', 'kini', 'gikompirmar', 'karong', 'Martes', ',', 'Marso', '28', ',', 'ni... | [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, 5, 6, 6, 6, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,060 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['MULI', ',', 'HAPPY', 'BIRTHDAY', 'TATAY', 'DIGONG', '!', ''', 'Gitimbaya', 'ni', 'Sen.', 'Si', 'Pang', 'si', 'Bong', 'Go', 'kaniadto.', 'Rodrigo', 'Duterte', 'sa', 'iyang', 'ika-78', 'n... | [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,061 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipaambit', 'ni', 'Issa', 'Pressman', 'ang', 'nindot', 'nga', 'mga', 'litrato', 'niya', 'kauban', 'sa', 'rumored', 'boyfriend', 'nga', 'si', 'James', 'Reid', 'sa', 'Instagram.', 'captio... | [0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 7, 0, 0, 1, 0] | cebuaner |
5,062 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['AMPING', 'PIRMI', ''', 'Sa', 'tweet', 'karong', 'Martes', ',', 'Marso', '28', ',', 'si', 'Senador', 'Sonny', 'Angara', 'mipaambit', 'og', 'mga', 'tips', 'gikan', 'sa', 'Department', 'of... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 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] | cebuaner |
5,063 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gisulayan', 'sa', 'Offshore', 'Combat', 'Force', 'sa', 'Philippine', 'Fleet', 'ang', 'ilang', 'bag-ong', 'nakuha', 'nga', 'Bullfighter', 'Chaff', 'Decoy', 'sakay', 'sa', 'BRP', 'Jose', ... | [0, 0, 3, 4, 4, 0, 3, 4, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 7, 8, 8, 8, 8, 8, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 5, 0] | cebuaner |
5,064 | 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', 'nationwide', 'poll', 'nga', 'gihimo', 'niadtong', 'Disyembre', '10-14', ',', '2022', 'sa', '1,200', 'ka', 'adult', 'nga', 'respondents', ',', '91', '%', 'kanila', 'mi... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,065 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Presidente', 'Bongbong', 'Marcos', 'mipahibalo', 'nga', 'ang', 'Pilipinas', '"', '[', 'mo', ']', 'wala', '"', 'sa', 'bisan', 'unsang', 'pakiglambigit', 'sa', 'ICC', 'human', 'kini... | [0, 0, 1, 2, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 0, 5, 0] | cebuaner |
5,066 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Pito', 'ka', 'mga', 'tawo', ',', 'lakip', 'ang', 'tulo', 'ka', 'mga', 'bata', ',', 'gipusil', 'ug', 'gipatay', 'ni', 'Audrey', 'Hale', ',', '28', ',', 'samtang', 'siya', 'misulod', 'sa'... | [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, 5, 6, 6, 0, 5, 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, 1, 2, 0, 1, 2, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0] | cebuaner |
5,067 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Human', 'gibasura', 'sa', 'International', 'Criminal', 'Court', '(', 'ICC', ')', 'ang', 'hangyo', 'sa', 'gobyerno', 'sa', 'Pilipinas', 'nga', 'suspensuhon', 'ang', 'imbestigasyon', 'sa'... | [0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,068 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ibinahagi', 'ni', 'dating', 'Senator', 'Kiko', 'Pangilinan', 'ang', 'isang', 'touching', 'encounter', 'niya', 'sa', 'isang', 'tagasuporta', 'na', 'umiyak', 'dahil', 'sa', 'pagkabigo', '... | [0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0] | cebuaner |
5,069 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'kagamhanan', 'sa', 'lalawigan', 'sa', 'Sugbo', 'nihulga', 'niadtong', 'Lunes', ',', 'Marso', '27', ',', 'nga', 'mopasaka', 'og', 'kasong', 'administratiba', 'ug', 'kriminal', 'ba... | [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 7, 0, 0, 0, 5, 0, 0, 0, 0, 3, 4, 4, 0, 0, 0, 1, 2, 2, 0] | cebuaner |
5,070 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'mismong', 'adlaw', 'sa', 'iyang', 'natawhan', 'karong', 'Marso', '28', ',', 'gibasura', 'sa', 'ICC', 'ang', 'apela', 'sa', 'gobyerno', 'sa', 'Pilipinas', 'nga', 'suspensuhon', 'ma... | [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, 0, 0, 0, 1, 2, 0] | cebuaner |
5,071 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dayun', 'gi-patyan', 'pa', 'gud', 'kag', 'electric', 'fan', 'bisag', 'natulog', ',', 'murag', 'dili', 'pamilya', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,072 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'mismong', 'adlaw', 'sa', 'iyang', 'adlawng', 'natawhan', 'karong', 'Marso', '28', ',', 'gibasura', 'sa', 'ICC', 'ang', 'apela', 'sa', 'gobyerno', 'sa', 'Pilipinas', 'nga', 'suspen... | [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, 0, 0, 0, 1, 2, 0] | cebuaner |
5,073 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dako', 'ang', 'papel', 'ni', 'kanhi', 'Presidente', 'Rodrigo', 'Duterte', 'sa', 'katumanan', 'sa', 'House', 'of', 'Hope', 'tungod', 'kay', 'nidonar', 'siya', 'og', 'house', 'and', 'lot'... | [0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
5,074 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DISGRASYA', 'SA', 'BACAY', ',', 'MINGLANILLA', 'CEBU', 'Mga', 'softdrinks', 'nausik', 'kay', 'natagak', 'sa', 'dalan', 'gikan', 'sa', 'delivery', 'truck', 'sa', 'Bacay', ',', 'Tulay', '... | [0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6] | cebuaner |
5,075 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mga', 'suspek', 'mao', 'ang', 'duha', 'ka', 'biyahero', 'nga', 'niagi', 'sa', 'AFP-PNP', 'Border', 'Control', 'Point', 'sa', 'Lasang', ',', 'Bunawan', ',', 'Davao', 'City', 'sayo... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 5, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,076 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['hambal', 'ni', 'Provincial', 'Administrator', 'Rayfrando', 'Diaz', 'II', ',', 'para', 'ini', 'sa', 'mga', 'magkadto', 'nga', 'turista', 'sa', 'probinsiya', 'atoll', 'sa', 'Semana', 'San... | [0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 7, 0, 0, 0, 0] | cebuaner |
5,077 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KADAKO', '!', 'Sa', 'imbestigasyon', 'sa', 'Bureau', 'of', 'Fire', 'Protection', '(', 'BFP', ')', 'Kapalong', 'nasayran', 'nga', '“electrical', 'ignition', 'cause', 'by', 'loose', 'conn... | [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] | cebuaner |
5,078 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipaambit', 'sa', 'Kapuso', 'actress', 'nga', 'si', 'Kyline', 'Alcantara', 'sa', 'iyang', 'Instagram', 'Story', 'ang', 'litrato', 'nila', 'uban', 'sa', ''Annaliza', ''', 'co-stars', 'ng... | [0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 7, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 1, 2, 0, 1, 2, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 1, 0, 0, 7, 0, 0] | cebuaner |
5,079 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gitandi', 'ni', 'House', 'tourism', 'committee', 'vice', 'chairman', 'Rep.', 'Marvin', 'Rillo', 'ang', 'oil', 'spill', 'sa', 'Oriental', 'Mindoro', 'sa', 'pagkalunod', 'sa', 'laing', 'o... | [0, 0, 3, 4, 4, 0, 0, 0, 1, 2, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 1, 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, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 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] | cebuaner |
5,080 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'Instagram', 'post', 'niadtong', 'weekend', ',', 'nag-pre-birthday', 'celebration', 'ang', 'South', 'Korean', 'star', 'atol', 'sa', 'ilang', 'BORN', 'PINK', 'concert', 'sa', 'Phili... | [0, 7, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 7, 8, 0, 0, 5, 6, 0] | cebuaner |
5,081 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Naghimo', 'og', 'survey', 'ang', 'Victoria', 'Milan', ',', 'usa', 'ka', 'dating', 'website', 'para', 'sa', 'mga', 'naay', 'nang', 'karelasyon', 'o', 'asawa', ',', 'og', 'nahibalan', 'an... | [0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
5,082 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'press', 'conference', ',', 'si', 'Justice', 'Secretary', 'Boying', 'Remulla', 'niingon', 'nga', 'duha', 'ngadto', 'sa', 'tulo', 'ka', 'tawo', 'ang', 'ilang', 'gikonsiderar', 'nga'... | [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, 5, 6, 0, 1, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,083 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nitubag', 'ang', 'vlogger', '/', 'entrepreneur', 'nga', 'si', 'Viy', 'Cortez', 'sa', 'usa', 'ka-komento', 'sa', 'usa', 'ka', 'netizen', 'nga', 'naingon', 'nga', 'dili', 'pa', 'raw', 'ka... | [0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 1, 0, 0, 0] | cebuaner |
5,084 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Malipayong', 'gi-share', 'sa', 'Kapuso', 'singer', 'nga', 'si', 'Golden', 'Cañedo', 'sa', 'iyang', 'Facebook', 'ang', 'video', 'nga', 'ni', 'attend', 'siya', 'sa', 'concert', 'sa', 'sik... | [0, 0, 0, 3, 0, 0, 0, 1, 2, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 3, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,085 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nipatigbabaw', 'ang', 'kasuko', 'sa', 'social', 'media', 'personality', 'ug', 'partner', 'ni', 'Whamos', 'Cruz', 'nga', 'si', 'Antonette', 'Gail', 'Del', 'Rosario', 'sa', 'gi-edit', 'ng... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 1, 2, 2, 2, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 1, 0] | cebuaner |
5,086 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Suno', 'sa', 'pila', 'ka', 'saksi', 'sang', 'aksidente', ',', 'gintinguhaan', 'sang', 'teenager', 'nga', 'kuhaon', 'ang', 'tumbler', 'nga', 'ginhaboy', 'sang', 'isa', 'sa', 'mga', 'tria... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,087 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Guys', ',', 'tip', 'naman', ':', 'Unsaon', 'pagsingil', 'sa', 'utang', 'sa', 'imong', 'ex', '?'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: C... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,088 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KANANG', 'LIMA', 'DAYON', 'KA', 'SONG', 'IMONG', 'GIBUTANG', 'SA', 'VIDEOKE', ',', 'BISAG', 'DILI', 'IKAW', 'ANG', 'NI-ARKILA'] Use the following schema: 1 = B-WIS: Beginning of a touri... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,089 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Unsay', 'sign', 'nga', 'dato', 'ang', 'pamilya', 'sa', 'pikas', 'cottage', '?'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,090 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Kini', 'gi-base', 'sa', 'gipaabot', 'nga', 'pagtungha', 'sa', 'crescent', 'moon', 'karong', 'tuiga.', 'Sa', 'panahon', 'sa', 'Ramadan', ',', 'ang', 'mga', 'Muslim', 'naglikay', 'sa', 'p... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 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] | cebuaner |
5,091 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DAOG', 'NA', 'SAB', 'Ang', 'Super', 'Lotto', '6', '/', '49', 'jackpot', 'prize', 'nadaogan', 'na', 'karong', 'Martes', ',', 'Marso', '21', ',', 'uban', 'sa', 'winning', 'number', 'combi... | [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, 0] | cebuaner |
5,092 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mokabat', 'sa', '25', 'ka', 'gidudahang', 'mga', 'manggugubat', 'ang', 'nasikop', 'sa', 'kapulisan', 'sa', 'giingong', 'illegal', 'nga', 'away', 'sa', 'Upper', 'Tabik', ',', 'Barangay',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0] | cebuaner |
5,093 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gihimakak', 'ni', 'Senador', 'Robin', 'Padilla', 'nga', 'interesado', 'siya', 'nga', 'mahimong', 'Bise', 'Presidente', 'sa', 'nasod', ',', 'apan', 'posibleng', 'modagan', 'siya', 'sa', ... | [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] | cebuaner |
5,094 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'video', 'ni', 'Negros', 'Oriental', '3rd', 'District', 'Rep.', 'Arnolfo', 'Teves', 'Jr.', 'post', 'sa', 'iyang', 'Facebook', ',', 'iyang', 'gibutyag', 'nga', 'posibleng', 'may', '... | [0, 0, 0, 5, 6, 6, 6, 0, 1, 2, 2, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
5,095 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mga', 'barangay', 'nga', 'gibantayan', 'sa', 'dakbayan', 'sa', 'Sugbo', 'mao', 'ang', 'Inayawan', ',', 'Bulacao', ',', 'Cogon', 'Pardo', ',', 'Toong', ',', 'Buhisan', ',', 'Tisa'... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 5, 0, 5, 0, 5, 6, 0, 5, 0, 5, 0, 5, 0, 5, 6, 0, 5, 0, 5, 0, 5, 0, 5, 6, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,096 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gitangtang', 'ni', 'Cebu', 'Gov', 'Gwendolyn', 'Garcia', 'ang', 'tanan', 'nga', 'nagkontrolar', 'sa', 'paglihok', 'sa', 'mga', 'kahayupan', 'ug', 'karne', 'sa', 'baboy', 'sa', 'probinsi... | [0, 0, 5, 0, 1, 2, 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] | cebuaner |
5,097 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Jail', 'Senior', 'Inspector', 'Ellen', 'Rose', 'Saragena', ',', 'hepe', 'sa', 'Bureau', 'of', 'Jail', 'Management', 'and', 'Penology', '(', 'BJMP', ')', '-Community', 'Relations',... | [0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 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] | cebuaner |
5,098 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ubos', 'sa', 'National', 'Pabahay', 'Para', 'sa', 'Pilipino', 'Housing', 'program', 'sa', 'administrasyong', 'Marcos', ',', '10', 'ka', 'mga', 'high-rise', 'building', ',', 'nga', 'adun... | [0, 0, 7, 8, 8, 8, 8, 8, 8, 0, 0, 1, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
5,099 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Matod', 'ni', 'Sen.', 'Sonny', 'Anagara', ',', 'dili', 'dayon', 'masulbad', 'ang', 'problema', 'sa', 'pampublikong', 'transportasyon', ',', 'tungod', 'kay', 'kinahanglan', 'pa', 'kini',... | [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, 7, 8, 8, 8, 0, 0, 0, 7, 8, 8, 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] | cebuaner |
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