{"id":"https://openalex.org/W2123431812","doi":"https://doi.org/10.1145/2382593.2382595","title":"Evaluating Textual Entailment Recognition for University Entrance Examinations","display_name":"Evaluating Textual Entailment Recognition for University Entrance Examinations","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W2123431812","doi":"https://doi.org/10.1145/2382593.2382595","mag":"2123431812"},"language":"en","primary_location":{"id":"doi:10.1145/2382593.2382595","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2382593.2382595","pdf_url":null,"source":{"id":"https://openalex.org/S56575750","display_name":"ACM Transactions on Asian Language Information Processing","issn_l":"1530-0226","issn":["1530-0226","1558-3430"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian Language Information Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004444958","display_name":"Yusuke Miyao","orcid":"https://orcid.org/0000-0002-0678-3400"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusuke Miyao","raw_affiliation_strings":["National Institute of Informatics","National Institute of Informatics,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"National Institute of Informatics,","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057192998","display_name":"Hideki Shima","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hideki Shima","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101586444","display_name":"Hiroshi Kanayama","orcid":"https://orcid.org/0000-0001-8183-5090"},"institutions":[{"id":"https://openalex.org/I4210145865","display_name":"IBM Research - Tokyo","ror":"https://ror.org/04915qk43","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210145865"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Kanayama","raw_affiliation_strings":["IBM Research - Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research - Tokyo","institution_ids":["https://openalex.org/I4210145865"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052956256","display_name":"Teruko Mitamura","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Teruko Mitamura","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6096,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.90676096,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"11","issue":"4","first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9955000281333923,"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":0.9955000281333923,"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":0.9939000010490417,"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/T13629","display_name":"Text Readability and Simplification","score":0.9876999855041504,"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/textual-entailment","display_name":"Textual entailment","score":0.9046310186386108},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7602170705795288},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7240568399429321},{"id":"https://openalex.org/keywords/logical-consequence","display_name":"Logical consequence","score":0.6940498352050781},{"id":"https://openalex.org/keywords/statement","display_name":"Statement (logic)","score":0.6169973611831665},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6065578460693359},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.580508828163147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5783672332763672},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5750064253807068},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.547187864780426},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5067446827888489},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5045489072799683},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.43157297372817993},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.20846819877624512},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07203322649002075}],"concepts":[{"id":"https://openalex.org/C95318506","wikidata":"https://www.wikidata.org/wiki/Q6588467","display_name":"Textual entailment","level":3,"score":0.9046310186386108},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602170705795288},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7240568399429321},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.6940498352050781},{"id":"https://openalex.org/C2777026412","wikidata":"https://www.wikidata.org/wiki/Q2684591","display_name":"Statement (logic)","level":2,"score":0.6169973611831665},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6065578460693359},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.580508828163147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5783672332763672},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5750064253807068},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.547187864780426},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5067446827888489},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5045489072799683},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.43157297372817993},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.20846819877624512},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07203322649002075},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2382593.2382595","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2382593.2382595","pdf_url":null,"source":{"id":"https://openalex.org/S56575750","display_name":"ACM Transactions on Asian Language Information Processing","issn_l":"1530-0226","issn":["1530-0226","1558-3430"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian Language Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W779780977","https://openalex.org/W1512105039","https://openalex.org/W2119465010","https://openalex.org/W2125885330","https://openalex.org/W2130158090","https://openalex.org/W2158710545","https://openalex.org/W2184774282","https://openalex.org/W2189143063","https://openalex.org/W2293949214","https://openalex.org/W2295486330","https://openalex.org/W2396767181","https://openalex.org/W2598654328","https://openalex.org/W3017975492","https://openalex.org/W3105439152"],"related_works":["https://openalex.org/W2169644218","https://openalex.org/W12963412","https://openalex.org/W2250460949","https://openalex.org/W3158371345","https://openalex.org/W3141423438","https://openalex.org/W2071098659","https://openalex.org/W2627035043","https://openalex.org/W4385571113","https://openalex.org/W4200417912","https://openalex.org/W1893429831"],"abstract_inverted_index":{"The":[0,171],"present":[1],"article":[2],"addresses":[3],"an":[4],"attempt":[5],"to":[6,13,52],"apply":[7],"questions":[8,46,101,125,140],"in":[9,21,34,77,84,97,157],"university":[10],"entrance":[11],"examinations":[12],"the":[14,31,35,90,103,124,166,176],"evaluation":[15,104,172],"of":[16,37,123,152,184],"textual":[17,72,107,130],"entailment":[18,73,108,131],"recognition.":[19],"Questions":[20],"several":[22],"fields,":[23],"such":[24,45,59],"as":[25,50,60,70,113],"history":[26],"and":[27,62,80,99,159],"politics,":[28],"primarily":[29],"test":[30],"examinee\u2019s":[32],"knowledge":[33],"form":[36],"choosing":[38],"true":[39],"statements":[40],"from":[41,56,138,141,162],"multiple":[42],"choices.":[43],"Answering":[44],"can":[47,67,126],"be":[48,68,127],"regarded":[49],"equivalent":[51],"finding":[53],"evidential":[54],"texts":[55],"a":[57,75,78,81,85,114,150,180,191],"textbase":[58,79],"textbooks":[61],"Wikipedia.":[63],"Therefore,":[64],"this":[65],"task":[66],"recast":[69],"recognizing":[71],"between":[74],"description":[76],"statement":[82],"given":[83],"question.":[86],"We":[87],"focused":[88],"on":[89],"National":[91],"Center":[92],"Test":[93],"for":[94,106,149,169],"University":[95],"Admission":[96],"Japan":[98],"converted":[100],"into":[102,129],"data":[105,145,167],"recognition":[109],"by":[110],"using":[111],"Wikipedia":[112],"textbase.":[115],"Consequently,":[116],"it":[117],"is":[118,147,187],"revealed":[119,174],"that":[120,175],"nearly":[121],"half":[122],"mapped":[128],"recognition;":[132],"941":[133],"text":[134],"pairs":[135],"were":[136],"created":[137],"404":[139],"six":[142,163],"subjects.":[143],"This":[144],"set":[146,168],"provided":[148],"subtask":[151],"NTCIR":[153],"RITE":[154],"(Recognizing":[155],"Inference":[156],"Text),":[158],"16":[160],"systems":[161],"teams":[164],"used":[165],"evaluation.":[170],"results":[173],"best":[177],"system":[178],"achieved":[179],"correct":[181],"answer":[182],"ratio":[183],"56%,":[185],"which":[186],"significantly":[188],"better":[189],"than":[190],"random":[192],"choice":[193],"baseline.":[194]},"counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}