Unnamed: 0 int64 0 335k | question stringlengths 17 26.8k | answer stringlengths 1 7.13k | user_parent stringclasses 29
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4,900 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Jeepney', 'New', 'Meta', ':', 'Pwede', 'na', 'musakay', 'tapad', 'sa', 'driver.', ':', ')'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Contin... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,901 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'traumatic', 'injury', 'maoy', 'usa', 'sa', 'mga', 'rason', 'nganong', 'nasakitan', 'ug', 'nasakitan', 'ang', 'mga', 'bata', ',', 'busa', 'atol', 'sa', 'umaabot', 'nga', 'National... | [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, 7, 8, 8, 8, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,902 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gihatagan', 'nimog', 'lato', 'lato', 'imong', 'uyab', ',', 'unya', 'gitoyo', ',', 'ikaw', 'pay', 'gilato-lato', '.'] 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 |
4,903 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['DECADE', 'OF', 'BEING', 'ARMY', 'Ang', 'Seoul', 'ug', 'ubang', 'mga', 'siyudad', 'sa', 'tibuok', 'kalibotan', 'nahimong', 'purpura', 'sa', 'pagsaulog', 'sa', '10', 'ka', 'tuig', 'nga', ... | [0, 0, 0, 3, 0, 5, 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, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0] | cebuaner |
4,904 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['KAMI', 'NA', 'LANG', 'ANG', 'I-BASH', 'NIYO'', 'Giingong', 'wala', 'makapugong', 'sa', 'pagka-emosyonal', 'ang', 'aktor', 'ug', 'bag-ong', 'TV', 'Host', 'sa', ''Eat', 'Bulaga', ''', 'ng... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,905 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gi-mingaw', 'nako', 'niya', ',', 'unsang', 'wrong', 'sent', 'message', 'idea', 'kaha', ',', 'ang', 'pwedeng', 'i-send', 'para', 'replyan', 'ko', 'niya.', '?', '?', '?'] Use the followin... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,906 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Duha', 'ka', 'bettors', 'ang', 'nakadaog', 'sa', 'jackpot', 'prize', 'sa', 'evening', 'draw', 'sa', 'Grand', 'Lotto', '6', '/', '55', 'sa', 'Philippine', 'Charity', 'Sweepstakes', 'Offi... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 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, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,907 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mga', 'trabahante', 'sa', 'miaging', 'buwan', 'nakadawat', 'sa', 'ilang', 'tseke', 'gikan', 'sa', 'DOLE', '7', 'sa', 'Cebu', 'City', 'isip', 'kabahin', 'sa', 'ilang', 'bayad.', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,908 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Kanang', 'kapila', 'namog-'Goodnight', ',', ''', 'pero', 'sige', 'gihapon', 'mo'g', 'istorya', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,909 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'iyang', 'bag-o', 'nga', 'co-sponsorship', ',', 'si', 'Senador', 'Sonny', 'Angara', 'mipadayag', 'og', 'paglaum', 'nga', 'ang', 'iyang', 'dekada', 'na', 'nga', 'Magna', 'Carta', 'o... | [0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 1, 0, 0, 3, 4, 4, 4, 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, 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... | cebuaner |
4,910 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Imohang', 'gipagahi', ',', 'unya', 'dili', 'nimo', 'kaunon.', '#', 'FilipinasBisaya'] 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] | cebuaner |
4,911 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['WELCOME', 'TO', 'THE', 'PH', '!', 'Nag-selfie', 'si', 'Samahang', 'Basketbol', 'ng', 'Pilipinas', '(', 'SBP', ')', 'Chairman', 'Sen.', 'Sonny', 'Angara', ',', 'uban', 'sa', 'NBA', 'lege... | [0, 0, 0, 5, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 1, 2, 0, 0, 0, 3, 0, 0, 0, 1, 2, 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, 1, 2, 0, 1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 7, 1, 0, 0, 7, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 1, 2, 0, 0, 0, 0, 3, 4... | cebuaner |
4,912 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Grabeng', 'init', ',', 'sign', 'na', 'ni', 'nga', 'magdungan', 'ta'g', 'ligo', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation o... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,913 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'hepe', 'sa', 'Abuyog', 'Police', 'Station', 'nga', 'si', 'Major', 'Luis', 'Hatton', 'niila', 'sa', 'biktima', 'nga', 'si', 'PFC', 'Aries', 'Ampoan', ',', '21', ',', 'sakop', 'sa'... | [0, 0, 0, 3, 4, 4, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 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, 3, 4, 0, 0, 1, 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, 3, 4, 0, 1, 0] | cebuaner |
4,914 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'bayronon', 'sa', 'business', 'ug', 'tourist', 'visitor', 'visas', '(', 'B1', '/', 'B2', ')', 'ug', 'uban', 'pang', 'non-petition', 'based', 'visas', 'sama', 'sa', 'student', 'ug'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,915 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'cash', 'assistance', 'ipadala', 'pinaagi', 'sa', 'City', 'Social', 'Welfare', 'Services', 'office.', 'Nakadawat', 'usab', 'og', 'nutribuns', 'ang', 'mga', 'nasunogan', 'sa', 'maa... | [0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 5, 0, 1, 2, 2, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0] | cebuaner |
4,916 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Magtag-ulan', 'na'g', 'usab', ',', 'wa', 'pa', 'ta', 'gihapon', 'nabasa', 'sa', 'dagat', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Cont... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,917 | 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', 'pamahayag', 'ni', 'Senador', 'Sonny', 'Angara', 'karong', 'Miyerkules', ',', 'Abril', '12', ',', 'bahin', 'sa', 'gihimong', 'pagtuon', 'sa', 'Commission', 'on', 'H... | [0, 0, 0, 0, 0, 0, 1, 2, 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, 3, 4, 4, 4, 4, 0, 3, 4, 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] | cebuaner |
4,918 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'National', 'Aeronautics', 'and', 'Space', 'Administration', '(', 'NASA', ')', 'mipaambit', 'sa', 'upat', 'ka', 'gagmay', 'nga', 'mga', 'lawak', 'nga', 'puy-anan', 'sa', 'mga', 'b... | [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, 5, 0] | cebuaner |
4,919 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['ingon', 'ni', 'City', 'Mayor', 'Jerry', 'Treñas', 'sa', 'usa', 'ka', 'mensahe', 'sa', 'Viber', 'sa', 'mga', 'miyembro', 'sa', 'media', 'Martes', 'sa', 'gabii.', 'Lakip', 'sa', 'nataptan... | [0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0, 3, 4, 4, 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, 0, 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 |
4,920 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mohimo', 'og', 'pahibalo', 'ang', 'Malacañang', 'sa', 'mosunod', 'nga', 'mga', 'adlaw', ',', 'ang', 'Presidential', 'Communications', 'Office', '(', 'PCO', ')', 'nagkanayon', 'karong', ... | [0, 0, 0, 0, 3, 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, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0] | cebuaner |
4,921 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Bacolod', 'City', 'Councilor', 'Jason', 'Villarosa', ',', 'chairman', 'sa', 'komitiba', 'sa', 'turismo', 'sa', 'Sangguniang', 'Panlungsod', ',', 'niingon', 'nga', 'una', 'na', 'ni... | [0, 5, 6, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0, 0, 0, 0, 7, 8, 0, 0, 0, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 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] | cebuaner |
4,922 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Naa', 'koy', 'kaila', 'nga', 'morag', 'motivational', 'speaker', 'sa', 'Facebook', ',', 'pero', 'judgmental', 'in', 'real', 'life', '.'] Use the following schema: 1 = B-WIS: Beginning o... | [0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,923 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Trending', 'sa', 'Twitter', 'ang', 'close-up', 'photo', 'sa', 'aktor', 'nga', 'si', 'Dingdong', 'Dantes', 'ug', 'BTS', 'member', 'nga', 'si', 'Jungkook.', 'Kini', 'ang', 'hulagway', 'ni... | [0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 3, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 7, 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 |
4,924 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Adunay', 'gibana-bana', 'nga', '97', 'ka', 'mga', 'pamilya', ',', 'nga', 'gilangkuban', 'sa', '335', 'ka', 'mga', 'indibidwal', ',', 'nga', 'makadawat', 'sa', 'pinansyal', 'nga', 'taban... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 3, 4, 4, 4, 4, 4, 4, 4, 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... | cebuaner |
4,925 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Hala', 'ka', ',', 'ikaw', 'ba', 'ni', 'Vivian', '?'] 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, 1, 0] | cebuaner |
4,926 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Evening', 'Prayer', '|', 'Abril', '13', ',', '2023', 'Lord', ',', 'salamat', 'kaayo', 'sa', 'tanang', 'grasya', 'nga', 'imong', 'gihatag.', 'Salamat', 'usab', 'sa', 'tibuok', 'adlaw', '... | [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, 1, 0, 0, 0] | cebuaner |
4,927 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Mandaue', 'City', 'Public', 'Employment', 'Service', 'Office', '(', 'PESO', ')', 'Chief', 'Musoline', 'Suliva', 'mitug-an', 'sa', 'mga', 'tigbalita', 'karong', 'Martes', ',', 'Abr... | [0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 2, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,928 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['OIL', 'INTERCEPTORS', 'SA', 'CCLEX', 'Ang', 'Metro', 'Pacific', 'Tollways', 'Corporation', 'nagbutang', 'ug', '13', 'ka', 'oil', 'interceptors', 'sa', 'Cebu-Cordova', 'Link', 'Expresswa... | [0, 0, 0, 5, 0, 3, 4, 4, 4, 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, 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] | cebuaner |
4,929 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mga', 'personahe', 'sa', 'Bureau', 'of', 'Fire', 'Protection', 'nagpahigayon', 'og', 'imbestigasyon', 'sa', 'sunog', 'nga', 'nahitabo', 'sa', 'merkado', 'publiko', 'sa', 'Baranga... | [0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 0] | cebuaner |
4,930 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gipasabot', 'sa', 'Metro', 'Pacific', 'Tollways', 'Corporation', '(', 'MPTC', ')', 'nga', 'gidili', 'ang', 'bisan', 'unsang', 'matang', 'sa', 'dula', ',', 'sama', 'sa', 'badminton', ','... | [0, 0, 3, 4, 4, 4, 4, 4, 4, 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, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0] | cebuaner |
4,931 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Abel', 'James', 'Monteagudo', ',', 'regional', 'director', 'sa', 'Department', 'Agriculture-Davao', ',', 'niingon', 'nga', 'ang', 'farm', 'gate', 'prices', 'sa', 'bugas', 'sa', 'r... | [0, 1, 2, 2, 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, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,932 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Tabangi', 'ko', '!'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a tourism-related entity; 3 = B-LOC: Beginning of a location ... | [0, 0, 0] | cebuaner |
4,933 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Napulog', 'pito', 'ka', 'mga', 'konsehal', 'sa', 'Davao', 'City', 'ang', 'nibotar', 'og', '"', 'yes', '"', 'sa', 'Anti-Bullying', 'Bill', 'ni', 'Konsehal', 'Enzo', 'Villafuerte', ',', '... | [0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,934 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['UNSAY', 'NAA', '?', 'Sa', 'Instagram', 'Story', 'ni', '2022', 'Miss', 'Universe', 'Philippines', 'Celeste', 'Cortesi', 'karong', 'Martes', ',', 'Abril', '11', ',', 'iyang', 'gipaambit',... | [0, 0, 0, 0, 7, 0, 0, 0, 3, 4, 4, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0] | cebuaner |
4,935 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['TRIGGER', 'WARNING', ':', 'RAPE', 'SLAY', 'Makaluluoy', 'ang', 'nahitabo', 'sa', 'usa', 'ka', '10-anyos', 'nga', 'batang', 'babaye', ',', 'kinsa', 'napalgang', 'patay', 'ug', 'walay', '... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 3, 4, 0, 3, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,936 | 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', 'karong', 'Huwebes', ',', 'Abril', '13', ',', 'nga', 'gisuspenso', 'si', 'Negros', 'Oriental', '3rd', 'District', 'Re... | [0, 0, 0, 0, 1, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 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, 5, 6, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
4,937 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Non-bailable', 'ang', 'kasong', 'pagpatay', 'nga', 'giatubang', 'nila', 'ni', 'kanhi', 'BuCor', 'Chief', 'Gerald', 'Bantag', 'ug', 'kanhi', 'deputy', 'Ricardo', 'Zulueta', 'sa', 'Muntin... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 2, 0, 0, 0, 1, 2, 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, 0, 0] | cebuaner |
4,938 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'Muntinlupa', 'Regional', 'Trial', 'Court', 'Branch', '206', 'nimando', 'usab', 'sa', 'pagdakop', 'kang', 'kanhi', 'Bureau', 'of', 'Corrections', '(', 'BuCor', ')', 'deputy', 'for... | [0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 3, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0] | cebuaner |
4,939 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Malipayon', 'ang', 'fans', 'ni', 'Bea', 'Alonzo', 'sa', 'bonding', 'nila', 'ni', 'Heart', 'Evangelista.', 'Si', 'Bea', 'ug', 'Heart', 'bag-o', 'lang', 'nagkita', 'og', 'balik', 'sa', 'p... | [0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 1, 2, 0, 1, 2, 2, 0, 1, 2, 0, 1, 2, 0, 0, 1, 2, 0] | cebuaner |
4,940 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Love', 'kuno', 'ko', 'niya', ',', 'kalit', 'nalang', 'ka-cold', ',', 'unsa', 'na', 'climate', 'change', '?'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,941 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Giingon', 'sa', 'ACT', 'kaniadtong', 'Lunes', ',', 'Abril', '10', 'nga', 'kini', 'nga', 'sugyot', 'nagsiguro', 'sa', 'duha', 'ka', 'bulan', 'nga', 'bakasyon', 'sa', 'eskuylahan', 'alang... | [0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 2] | cebuaner |
4,942 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Evening', 'Prayer', '|', 'Abril', '12', ',', '2023', 'Lord', ',', 'salamat', 'kaayo', 'sa', 'tanang', 'grasya', 'nga', 'imong', 'gihatag.', 'Salamat', 'usab', 'sa', 'tibuok', 'adlaw', '... | [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, 1, 0, 0, 0] | cebuaner |
4,943 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Tungod', 'kay', 'hapit', 'na', 'mabutang', 'sa', 'peligro', 'ang', 'Tukomi', 'pranksters', ',', 'giawhag', 'sa', 'Davao', 'City', 'Public', 'Safety', 'and', 'Security', 'Office', '(', '... | [0, 0, 0, 0, 0, 0, 0, 0, 3, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 2, 0, 0, 0, 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... | cebuaner |
4,944 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'post', 'sa', 'Facebook', 'nagpakita', 'sa', 'litrato', 'sa', 'babaye', 'uban', 'sa', 'iyang', 'ex-boyfriend', ',', 'nga', 'grayscaled—bisan', 'dili', 'patay—sama', 'sa', 'uso', '... | [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] | cebuaner |
4,945 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Lapulapu', 'City', 'Councilor', 'Annabeth', 'Cuizon', ',', 'chairperson', 'sa', 'Committee', 'on', 'Social', 'Services', ',', 'niingon', 'nga', 'ang', 'educational', 'assistance',... | [0, 3, 4, 0, 1, 2, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 5, 6, 0, 1, 2, 0, 0, 0, 0, 7, 0] | cebuaner |
4,946 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gidudahan', 'nga', 'selos', 'ang', 'hinungdan', 'sa', 'pag-atake', 'sa', 'suspek', ',', 'nadestino', 'sa', 'Magpet', 'Municipal', 'Police', ',', 'sa', 'iyang', 'kauban', 'karong', 'Mart... | [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] | cebuaner |
4,947 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'kuha', 'sa', 'CCTV', ',', 'makita', 'nga', 'niagi', 'ang', 'saag', 'nga', 'iro', 'luyo', 'sa', 'ginikanan', 'sa', 'bata', 'nga', 'parehong', 'nag-duty', 'sa', 'gasolinahan.', 'Mid... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,948 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'report', 'sa', 'kapulisan', ',', 'ang', 'unom', 'ka', 'managhigala', 'gikan', 'sa', 'piknik', 'paingon', 'na', 'untang', 'mopauli', 'dihang', 'mibundak', 'ang', 'kusog', 'nga', 'u... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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] | cebuaner |
4,949 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nganong', 'mangita', 'paman', 'ko'g', 'mag', 'pakatawa', 'nako', ',', 'nga', 'mo', 'katawa', 'raman', 'ko'g', 'ako', 'ra', 'isa', '.'] Use the following schema: 1 = B-WIS: Beginning of ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,950 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'Amerika', 'ug', 'Pilipinas', 'nagsugod', 'karong', 'Martes', ',', 'Abril', '11', ',', 'ang', 'kinadak-ang', 'combat', 'exercises', 'tali', 'sa', 'duha', 'ka', 'nasod', ',', 'nga'... | [0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 5, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,951 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SAKTO', '!', 'Nalipay', 'ang', 'mga', 'netizen', 'sa', 'pamahayag', 'sa', 'Kapamilya', 'actress', 'nga', 'si', 'Belle', 'Mariano', 'bahin', 'sa', 'paglungtad', 'sa', 'mga', 'bashers', '... | [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, 1, 2, 0, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
4,952 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Si', 'Talisay', 'City', 'Mayor', 'Gerald', 'Anthony', ''Samsam', ''', 'Gullas', 'niingon', 'nga', 'bisan', 'pa', 'sa', 'kamatuoran', 'nga', 'ang', 'Metro', 'Cebu', 'dili', 'direktang', ... | [0, 5, 6, 0, 1, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 5, 0] | cebuaner |
4,953 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nagplano', 'mi', 'nga', 'mag-swimming', ',', 'pero', 'wa', 'mi', 'ka-plano', 'unsaon', 'pagdayon', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,954 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Opisyal', 'nga', 'gianunsyo', 'sa', '19-anyos', 'nga', 'British', 'actress', 'ni', 'Millie', 'Bobby', 'Brown', 'sa', 'Instagram', 'ang', 'iyang', 'engagement', 'ngadto', 'kang', 'Jake',... | [0, 0, 0, 0, 0, 0, 7, 0, 0, 1, 2, 2, 0, 7, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 7, 0, 0, 1, 0, 0, 0, 0, 0, 0, 7, 0, 7, 8, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 2, 0] | cebuaner |
4,955 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['LOOK', ':', 'Sa', 'pagkakaron', 'adunay', 'sunog', 'nga', 'nahitabo', 'sa', 'Bagua', '1', '(', 'Manday', 'area', ')', ',', 'Cotabato', 'City.', 'Padayon', 'nga', 'gipalong', 'sa', 'BFP'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 3, 4, 0, 0, 0] | cebuaner |
4,956 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Trending', 'ang', 'post', 'sa', 'Facebook', 'user', 'nga', 'si', 'Pinky', 'Uriarte', 'nga', 'nagpakita', 'sa', 'video', 'sa', 'usa', 'ka', 'ginang', 'nga', 'gitabangan', 'sa', 'pagpanga... | [0, 0, 0, 0, 7, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 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] | cebuaner |
4,957 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gisurpresa', 'sa', 'aktres', 'nga', 'si', 'Kiray', 'Celis', 'ang', 'iyang', 'inahan', 'sa', 'iyang', 'adlawng', 'natawhan', 'og', 'P1', 'Million.', 'Suma', 'pa', 'sa', 'aktres', ',', 'g... | [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, 1, 0] | cebuaner |
4,958 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'advisory', 'sa', 'Municipal', 'Environment', 'and', 'Natural', 'Resources', 'Office', '(', 'MENRO', ')', 'sa', 'Balamban', ',', 'Cebu', ',', 'sugod', 'Mayo', '2', ',', 'gidili', '... | [0, 0, 0, 3, 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, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 7, 8, 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] | cebuaner |
4,959 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Evening', 'Prayer', '|', 'Abril', '11', ',', '2023', 'Lord', ',', 'salamat', 'kaayo', 'sa', 'tanang', 'grasya', 'nga', 'imong', 'gihatag.', 'Salamat', 'usab', 'sa', 'pagpahulay', ',', '... | [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, 1, 0, 0, 0] | cebuaner |
4,960 | 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', 'Rich', 'Kid', 'imong', 'ka', 'work', '?'] 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, 0, 0, 0, 0] | cebuaner |
4,961 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'Davao', 'City', 'Public', 'Safety', 'and', 'Security', 'Office', 'nagkanayon', 'nga', 'sa', 'kinatibuk-an', 'malinawon', 'ang', 'selebrasyon', 'sa', 'Semana', 'Santa', 'sa', 'siy... | [0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 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, 7, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,962 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'biktima', 'giila', 'nga', 'si', 'Alvin', 'Guia', ',', 'nagtrabaho', 'isip', 'production', 'worker', 'sa', 'Mandaue', 'City.', 'Sa', 'report', 'sa', 'kapulisan', ',', 'ang', 'iyan... | [0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0] | cebuaner |
4,963 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Matud', 'ni', 'Police', 'Lt.', 'Si', 'Colonel', 'Randy', 'Caballes', ',', 'hepe', 'sa', 'Talisay', 'City', 'Police', 'Station', ',', 'niila', 'sa', 'mga', 'biktima', 'nga', 'sila', 'si'... | [0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 3, 4, 4, 4, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,964 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'post', 'sa', 'netizen', 'nga', 'si', 'Richard', 'Go', 'bag-o', 'lang', 'nag-viral', 'sa', 'Facebook', 'niadtong', '2019', 'nga', 'nag-feature', 'sa', 'mga', 'litrato', 'nga', 'iy... | [0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 5, 6, 0, 5, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 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, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,965 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'Veteran', ''s', 'Monument', 'sa', 'junction', 'sa', 'Roxas', 'Avenue-Ponciano', 'Reyes', 'Street', 'sa', 'Davao', 'City', ',', 'kanunay', 'nga', 'mapahiyumon', 'ang', '99-anyos', ... | [0, 5, 6, 6, 0, 0, 0, 5, 6, 6, 6, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 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, 1, 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, 5, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0... | cebuaner |
4,966 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Niadtong', 'Abril', '4', ',', 'si', 'Cebu', 'Governor', 'Gwendolyn', 'Garcia', 'niluwat', 'og', 'Executive', 'Order', '(', 'EO', ')', 'No.', '11', 'nga', 'molugway', 'og', 'dugang', '15... | [0, 0, 0, 0, 0, 5, 0, 1, 2, 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, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 0] | cebuaner |
4,967 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Pipila', 'ka', 'buwan', 'human', 'sa', 'kontrobersyal', 'ug', 'viral', 'nga', 'icing-smearing', 'incident', 'nga', 'naglambigit', 'sa', 'host-vlogger', 'nga', 'si', 'Alex', 'Gonzaga', '... | [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] | cebuaner |
4,968 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Kanang', 'bakasyon', 'nga', 'taman', 'kalendaryo', 'lang', '.'] 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, 0, 0] | cebuaner |
4,969 | 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.', 'Abegael', 'Donasco', ',', 'deputy', 'police', 'chief', 'sa', 'dakbayan', 'sa', 'Talisay', ',', 'kinsa', 'nidakop', 'sa', 'tinun-an', 'human', 'nitaho', 'an... | [0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 0] | cebuaner |
4,970 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nganong', 'wala', 'nay', 'motivational', 'quotes', 'sa', 'akong', 'timeline', 'dili', 'na', 'pud', 'ba', 'ninyo', 'kaya', '?'] Use the following schema: 1 = B-WIS: Beginning of a touris... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,971 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['BUS', 'NAGBUNGGO', 'ANG', 'JEEPNEY', 'Tulo', 'ka', 'tawo', 'ang', 'naangol', 'human', 'nabangga', 'ang', 'usa', 'ka', 'pampasaherong', 'bus', 'sa', 'usa', 'ka', 'pampasaherong', 'jeep',... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,972 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dili', 'man', 'ko', 'anad', 'nga', 'manuyo', ',', 'anad', 'man', 'ko', 'mang-away', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuat... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,973 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Lima', 'ka', 'miyembro', 'sa', 'usa', 'ka', 'pamilya', 'ang', 'namatay', 'sa', 'lungsod', 'sa', 'Pozorrubio', ',', 'Pangasinan', 'niadtong', 'Lunes', ',', 'Abril', '3', ',', 'human', 'n... | [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, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,974 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'pagbalik', 'sa', 'programa', 'nga', ''Face', '2', 'Face', ''', 'sa', 'TV5', ',', 'ang', 'host-singer', 'ba', 'nga', 'si', 'Karla', 'Estrada', 'ang', 'angayan', 'nga', 'mahimong', ... | [0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 3, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,975 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Indian', 'national', 'nga', 'giilang', 'si', 'Ranjit', 'Singh', ',', '46-anyos', ',', 'sa', 'Barangay', 'Perrelos', ',', 'dakbayan', 'sa', 'Carcar', ',', 'Cebu', 'tungod', 'sa', 'giingo... | [7, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 5, 6, 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, 1, 2, 2, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,976 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['“My', 'home', ',', '”', 'caption', 'ni', 'Barbie', 'Forteza', 'sa', 'iyang', 'post', ',', 'nga', 'gireplyan', 'ni', 'Jak', 'Roberto', 'og', '“The', 'best', '!', '❤️', '.', '"'] Use the ... | [0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,977 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Isa', 'ka', 'minor', 'de', 'edad', 'nga', 'babaye', 'nga', 'naghimo', 'sa', 'April', 'Fools', ''', 'prank', 'nangayo', 'og', 'pasaylo', 'sa', 'publiko', 'nga', 'nag-ingon', 'nga', 'siya... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 3, 4, 4, 0, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,978 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Buyag', 'uy', 'unsa', 'mani', 'akong', 'mga', 'nakita', 'mag', 'semana', 'santa', 'na', 'ra', 'ba'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,979 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['REASON', 'WHY', 'NEVER', 'AKO', 'SUMALI', 'SA', 'MGA', 'HIGH', 'SCHOOL', 'REUNIONS'', 'DABAWENYA', 'content', 'creator', 'nga', 'si', 'Karel', 'Kat', 'Lopez', 'mipaambit', 'sa', 'iyang'... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 1, 2, 2, 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, 1, 0, 0, 0, 0, 7, 0, 0] | cebuaner |
4,980 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Kapag', 'terno', 'iyahang', 'hambag', 'og', 'lunch', 'box', '.'] 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, 0, 0, 0] | cebuaner |
4,981 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Lord', ',', 'salamat', 'kaayo', 'sa', 'tanang', 'grasya', 'nga', 'imong', 'gihatag', 'nako', 'karon.', 'Salamat', 'usab', 'sa', 'pagpahulay', ',', 'hinaut', 'nga', 'bantayan', 'mo', 'ka... | [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, 1, 0] | cebuaner |
4,982 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Dili', 'lang', 'Holy', 'Week', 'akoang', 'gihuwat', ',', 'pati', 'pod', 'imohang', 'chat', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Co... | [0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,983 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Kanang', 'todo-kag', 'birit', 'sa', 'videoke', 'nya', 'naay', 'makig', 'tunga', '.'] 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] | cebuaner |
4,984 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['INIT', 'KAAYO', 'SA', 'MACTAN', 'Ang', 'PAGASA-Mactan', 'nitala', 'og', 'heat', 'index', 'nga', '36', '°C', 'sa', 'dakbayan', 'sa', 'Sugbo', 'alas', '12', 'sa', 'udto', 'Martes', ',', '... | [0, 0, 0, 5, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,985 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Nitaas', 'ang', 'presyo', 'sa', 'sikat', 'nga', 'hikay', 'pag', 'semana', 'santa'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,986 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'Meta', 'CEO', 'nga', 'si', 'Mark', 'Zuckerberg', 'maoy', 'sentro', 'sa', 'atensyon', 'online', 'human', 'ang', 'iyang', 'AI-generated', 'nga', 'mga', 'litrato', 'nga', 'nagpakita... | [0, 3, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,987 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['SAN', 'KA', 'PUNTA', '?', 'TO', 'THE', 'MOON', 'LITERAL', 'Ang', 'misyon', 'naglakip', 'sa', 'tulo', 'ka', 'mga', 'astronaut', 'sa', 'NASA', ',', 'lakip', 'ang', 'unang', 'babaye', ',',... | [0, 0, 0, 0, 0, 0, 5, 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, 5, 0, 0, 0, 0, 0, 7, 0, 0, 0, 5, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,988 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'impormasiyon', ',', 'naglakaw', 'ang', 'biktima', 'nga', 'si', 'alyas', ''Dodong', ''', 'paingon', 'sa', 'merkado', 'sa', 'Bankerohan', 'dihang', 'kalit', 'lang', 'gibunalan', 'sa... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,989 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'mga', 'operatiba', 'sa', 'Philippine', 'Drug', 'Enforcement', 'Agency', '(', 'PDEA', ')', '-Cebu', 'Provincial', 'Office', ',', 'ug', 'Cebu', 'City', 'Police', 'Office', 'Station... | [0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 3, 4, 4, 4, 4, 4, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,990 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Still', 'rocking', 'at', '75', '!', 'Gawas', 'kang', 'Presidente', 'Bongbong', 'Marcos', ',', 'ang', 'ubang', 'mga', 'VIP', 'mitambong', 'usab', 'sa', 'party', 'ni', 'Finance', 'Secreta... | [0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,991 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Suma', 'pa', 'ni', 'Aljur', 'nga', 'ang', 'iyang', '"', 'biggest', 'mistake', '"', 'mao', 'ang', 'pagkapakyas', 'sa', 'paggahin', 'og', 'igong', 'panahon', 'o', 'oras', 'uban', 'ni', 'K... | [0, 0, 0, 1, 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] | cebuaner |
4,992 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'pagpatay', 'sa', '22', 'anyos', 'nga', 'tinun-an', 'sa', 'De', 'La', 'Salle', 'University-Dasmariñas', 'sa', 'lalawigan', 'sa', 'Cavite', 'subling', 'nakaduso', 'kang', 'Senador'... | [0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 0, 0, 0, 5, 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, 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, 5, 6, 6, 6, 6, 0, 0, 0, 0, 1, 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... | cebuaner |
4,993 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sa', 'iya', 'ID', ',', 'ginkilala', 'ang', 'biktima', 'kay', 'Christine', 'Gabayeron', 'sang', 'Barangay', 'San', 'Vicente', ',', 'Jaro', ',', 'Iloilo', 'City', ',', 'apang', 'suno', 's... | [0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 5, 6, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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 |
4,994 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Mao', 'diayng', 'init', 'kaau', 'ky', 'naay', 'nagpataka', 'og', 'ampo', '.'] Use the following schema: 1 = B-WIS: Beginning of a tourism-related entity; 2 = I-WIS: Continuation of a to... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,995 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['“This', '(', 'inquiry', ')', 'is', 'to', 'clarify', 'issues.', 'Wala', 'itong', 'kinalaman', 'sa', 'kaso', 'ng', 'ICC', '(', 'International', 'Criminal', 'Court', ')', ',', '”', 'ani', ... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0] | cebuaner |
4,996 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Ang', 'Police', 'Regional', 'Office-Davao', 'Region', '(', 'PRO-Davao', ')', 'mitaho', 'nga', 'ang', 'mga', 'kaso', 'sa', 'pagpanglugos', 'sa', 'rehiyon', 'nakapaalarma', ',', 'human', ... | [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, 3, 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] | cebuaner |
4,997 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Sumala', 'sa', 'Philippine', 'National', 'Police', '(', 'PNP', ')', 'Directorate', 'for', 'Operation', ',', 'mokabat', 'sa', '38,387', 'ka', 'mga', 'pulis', 'ang', 'ipakatap', 'alang', ... | [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 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... | cebuaner |
4,998 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Delikado', 'jud', 'nang', 'reto-reto', ',', 'dira', 'man', 'ko', 'nadali.', '#', 'PilipinasToday', '#', 'Bench', '#', 'WiHajoon'] Use the following schema: 1 = B-WIS: Beginning of a tou... | [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | cebuaner |
4,999 | What is the tagged array of these Cebuano tokenized words using the BIO encoding schema for the named entity recognition (NER) task? ['Gibutyag', 'sa', 'aktor', 'nga', 'si', 'JM', 'De', 'Guzman', 'nga', 'nag', ''self-destruct', ''', 'siya', 'human', 'sa', 'iyang', '"', 'sakit', '"', 'nga', 'panagbuwag', 'sa', 'iyang', ... | [0, 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0] | cebuaner |
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