{"id":"https://openalex.org/W2130237711","doi":"https://doi.org/10.3115/v1/d14-1070","title":"A Neural Network for Factoid Question Answering over Paragraphs","display_name":"A Neural Network for Factoid Question Answering over Paragraphs","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2130237711","doi":"https://doi.org/10.3115/v1/d14-1070","mag":"2130237711"},"language":"en","primary_location":{"id":"doi:10.3115/v1/d14-1070","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1070","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3115/v1/d14-1070","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082767919","display_name":"Mohit Iyyer","orcid":"https://orcid.org/0000-0001-7340-0804"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohit Iyyer","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081307846","display_name":"Jordan Boyd\u2010Graber","orcid":"https://orcid.org/0000-0002-7770-4431"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jordan Boyd-Graber","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084282814","display_name":"Leonardo Claudino","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leonardo Claudino","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059955534","display_name":"Richard Socher","orcid":"https://orcid.org/0000-0002-3577-639X"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard Socher","raw_affiliation_strings":["University of Colorado \u2010 Boulder"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Colorado \u2010 Boulder","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019928111","display_name":"Hal Daum\u00e9","orcid":"https://orcid.org/0000-0002-3760-345X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hal Daum\u00e9 III","raw_affiliation_strings":["University of Maryland, College Park, College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":31.2224,"has_fulltext":false,"cited_by_count":325,"citation_normalized_percentile":{"value":0.99863855,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"633","last_page":"644"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.8634072542190552},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8585021495819092},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7453518509864807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7419214844703674},{"id":"https://openalex.org/keywords/principle-of-compositionality","display_name":"Principle of compositionality","score":0.6232729554176331},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.6127406358718872},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5947179198265076},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5470954775810242},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.45521801710128784},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41673359274864197},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4112780690193176},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3578190803527832},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.15134942531585693}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8634072542190552},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8585021495819092},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7453518509864807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7419214844703674},{"id":"https://openalex.org/C121375916","wikidata":"https://www.wikidata.org/wiki/Q936559","display_name":"Principle of compositionality","level":2,"score":0.6232729554176331},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.6127406358718872},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5947179198265076},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5470954775810242},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.45521801710128784},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41673359274864197},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4112780690193176},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3578190803527832},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.15134942531585693},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3115/v1/d14-1070","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1070","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.654.8794","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.654.8794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aclweb.org/anthology/D/D14/D14-1070.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.672.5484","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.672.5484","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.umd.edu/%7Emiyyer/pubs/2014_qb_rnn.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.682.5519","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.5519","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://emnlp2014.org/papers/pdf/EMNLP2014070.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/d14-1070","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1070","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W16319610","https://openalex.org/W21006490","https://openalex.org/W42251416","https://openalex.org/W71795751","https://openalex.org/W1506522508","https://openalex.org/W1508977358","https://openalex.org/W1592588918","https://openalex.org/W1597195725","https://openalex.org/W1614298861","https://openalex.org/W1934849960","https://openalex.org/W1975073368","https://openalex.org/W1987063155","https://openalex.org/W2100693535","https://openalex.org/W2104518905","https://openalex.org/W2106390866","https://openalex.org/W2118772635","https://openalex.org/W2120735855","https://openalex.org/W2122865749","https://openalex.org/W2125573226","https://openalex.org/W2126776599","https://openalex.org/W2127426251","https://openalex.org/W2131744502","https://openalex.org/W2133280805","https://openalex.org/W2137607259","https://openalex.org/W2146502635","https://openalex.org/W2149557440","https://openalex.org/W2150295085","https://openalex.org/W2168963845","https://openalex.org/W2187089797","https://openalex.org/W2251623545","https://openalex.org/W2251738400","https://openalex.org/W2251939518","https://openalex.org/W2964106094","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3095531775","https://openalex.org/W2608109911","https://openalex.org/W2795843251","https://openalex.org/W2160451571","https://openalex.org/W3204607391","https://openalex.org/W2964413124","https://openalex.org/W4388937922","https://openalex.org/W3113264705","https://openalex.org/W2495256954","https://openalex.org/W2259317772"],"abstract_inverted_index":{"Text":[0],"classification":[1],"methods":[2,22],"for":[3],"tasks":[4],"like":[5],"factoid":[6],"question":[7,26],"answering":[8],"typi-cally":[9],"use":[10],"manually":[11],"defined":[12],"string":[13],"match-ing":[14],"rules":[15],"or":[16],"bag":[17],"of":[18,39,68],"words":[19,32],"representa-tions.":[20],"These":[21],"are":[23,37],"ineffective":[24],"when":[25,101],"text":[27],"contains":[28],"very":[29],"few":[30],"individual":[31],"(e.g.,":[33],"named":[34],"entities)":[35],"that":[36,50,87],"indicative":[38],"the":[40,108],"answer.":[41],"We":[42,60],"introduce":[43],"a":[44,66,71],"recursive":[45],"neural":[46],"network":[47],"(rnn)":[48],"model":[49,96],"can":[51],"reason":[52,92],"over":[53],"such":[54],"input":[55],"by":[56],"modeling":[57],"textual":[58],"composition-ality.":[59],"apply":[61],"our":[62],"model,":[63],"qanta,":[64],"to":[65,91],"dataset":[67],"questions":[69],"from":[70],"trivia":[72],"competition":[73],"called":[74],"quiz":[75],"bowl.":[76],"Unlike":[77],"previous":[78],"rnn":[79],"models,":[80],"qanta":[81],"learns":[82],"word":[83],"and":[84],"phrase-level":[85],"representations":[86],"combine":[88],"across":[89],"sentences":[90],"about":[93],"entities.":[94],"The":[95],"outperforms":[97],"multiple":[98],"baselines":[99],"and,":[100],"combined":[102],"with":[103],"information":[104],"retrieval":[105],"methods,":[106],"ri-vals":[107],"best":[109],"human":[110],"players.":[111],"1":[112]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":32},{"year":2019,"cited_by_count":36},{"year":2018,"cited_by_count":46},{"year":2017,"cited_by_count":49},{"year":2016,"cited_by_count":60},{"year":2015,"cited_by_count":38},{"year":2014,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}