{"id":"https://openalex.org/W3034862440","doi":"https://doi.org/10.24963/ijcai.2020/546","title":"Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation Extraction","display_name":"Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation Extraction","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3034862440","doi":"https://doi.org/10.24963/ijcai.2020/546","mag":"3034862440"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/546","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/546","pdf_url":"https://www.ijcai.org/proceedings/2020/0546.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0546.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101615683","display_name":"Tianyang Zhao","orcid":"https://orcid.org/0000-0001-5973-2044"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyang Zhao","raw_affiliation_strings":["State Key Lab of Software Development Environment, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100748465","display_name":"Zhao Yan","orcid":"https://orcid.org/0000-0002-0468-8565"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Yan","raw_affiliation_strings":["Tencent Cloud Xiaowei, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Cloud Xiaowei, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011542448","display_name":"Yunbo Cao","orcid":"https://orcid.org/0009-0005-2558-5206"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunbo Cao","raw_affiliation_strings":["Tencent Cloud Xiaowei, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Cloud Xiaowei, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036786337","display_name":"Zhoujun Li","orcid":"https://orcid.org/0000-0002-9603-9713"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhoujun Li","raw_affiliation_strings":["State Key Lab of Software Development Environment, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.7499,"has_fulltext":false,"cited_by_count":70,"citation_normalized_percentile":{"value":0.96979063,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3948","last_page":"3954"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9998000264167786,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.828234076499939},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7823083400726318},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.7745312452316284},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6737878918647766},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.610042929649353},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5420104265213013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5177218317985535},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5130249857902527},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.49528709053993225},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4893607497215271},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4851275384426117},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45600685477256775},{"id":"https://openalex.org/keywords/meaning","display_name":"Meaning (existential)","score":0.4444178342819214},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.4207330048084259},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.41482847929000854},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.3985513746738434},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3945011794567108},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32736480236053467},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22659236192703247},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11710435152053833},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09364789724349976}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.828234076499939},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7823083400726318},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.7745312452316284},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6737878918647766},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.610042929649353},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5420104265213013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5177218317985535},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5130249857902527},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.49528709053993225},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4893607497215271},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4851275384426117},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45600685477256775},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.4444178342819214},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.4207330048084259},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.41482847929000854},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3985513746738434},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3945011794567108},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32736480236053467},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22659236192703247},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11710435152053833},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09364789724349976},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","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:10.24963/ijcai.2020/546","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/546","pdf_url":"https://www.ijcai.org/proceedings/2020/0546.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/546","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/546","pdf_url":"https://www.ijcai.org/proceedings/2020/0546.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1363696916","display_name":"\u793e\u4ea4\u7f51\u7edc\u4e2d\u70ed\u70b9\u8bdd\u9898\u68c0\u6d4b\u4e0e\u4f20\u64ad\u5206\u6790\u7814\u7a76","funder_award_id":"61370126","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1835827439","display_name":null,"funder_award_id":"Grant No.SKLSDE-2019ZX-17","funder_id":"https://openalex.org/F4320326978","funder_display_name":"State Key Laboratory of Software Development Environment"},{"id":"https://openalex.org/G2219711069","display_name":null,"funder_award_id":"SKLSDE-2019ZX-17","funder_id":"https://openalex.org/F4320326978","funder_display_name":"State Key Laboratory of Software Development Environment"},{"id":"https://openalex.org/G2323930268","display_name":null,"funder_award_id":"U1636211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2871100745","display_name":null,"funder_award_id":"Grant No.BAICIT-2016001","funder_id":"https://openalex.org/F4320333617","funder_display_name":"Beijing Advanced Innovation Center for Imaging Technology"},{"id":"https://openalex.org/G5257086154","display_name":null,"funder_award_id":"Grant Nos.U1636211, 61672081, 61370126","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5485939886","display_name":null,"funder_award_id":"BAICIT-2016001","funder_id":"https://openalex.org/F4320333617","funder_display_name":"Beijing Advanced Innovation Center for Imaging Technology"},{"id":"https://openalex.org/G7104496898","display_name":"\u793e\u533a\u95ee\u7b54\u7cfb\u7edf\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61672081","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7505276045","display_name":null,"funder_award_id":"2016001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326978","display_name":"State Key Laboratory of Software Development Environment","ror":null},{"id":"https://openalex.org/F4320333617","display_name":"Beijing Advanced Innovation Center for Imaging Technology","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3034862440.pdf","grobid_xml":"https://content.openalex.org/works/W3034862440.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1996787131","https://openalex.org/W2132516856","https://openalex.org/W2134033474","https://openalex.org/W2251091211","https://openalex.org/W2515462165","https://openalex.org/W2551396370","https://openalex.org/W2578454709","https://openalex.org/W2741956709","https://openalex.org/W2759056771","https://openalex.org/W2798393196","https://openalex.org/W2798734500","https://openalex.org/W2798858969","https://openalex.org/W2799125718","https://openalex.org/W2896457183","https://openalex.org/W2919420119","https://openalex.org/W2949212908","https://openalex.org/W2949922292","https://openalex.org/W2951231735","https://openalex.org/W2962718483","https://openalex.org/W2962881743","https://openalex.org/W2963339397","https://openalex.org/W2963341956","https://openalex.org/W2963547127","https://openalex.org/W2963602416","https://openalex.org/W2963748441","https://openalex.org/W2963769536","https://openalex.org/W2964167098","https://openalex.org/W3035625205","https://openalex.org/W4288548690","https://openalex.org/W4293350112","https://openalex.org/W4295253143"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W1984061923","https://openalex.org/W2444550338","https://openalex.org/W2369351710","https://openalex.org/W2594363579"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"cast":[2],"the":[3,20,34,47,76,148,157],"entity-relation":[4,79],"extraction":[5,80],"to":[6,32,59,68,94,105,112,124,160],"a":[7,29,87,114],"multi-turn":[8],"question":[9,31,84,89],"answering":[10,90,100],"(QA)":[11],"task":[12],"and":[13,38,65,98,119,130,139,165],"provide":[14],"an":[15,136],"effective":[16],"solution":[17],"based":[18],"on":[19,163,168],"machine":[21],"reading":[22],"comprehension":[23],"(MRC)":[24],"models.":[25],"However,":[26],"they":[27],"use":[28],"single":[30],"characterize":[33],"meaning":[35],"of":[36,46,49,116],"entities":[37],"relations,":[39],"which":[40,62,155],"is":[41,63,92,172],"intuitively":[42],"not":[43],"enough":[44],"because":[45],"variety":[48],"context":[50],"semantics.":[51],"Meanwhile,":[52],"existing":[53,77],"models":[54],"enumerate":[55],"all":[56],"relation":[57,131,158],"types":[58],"generate":[60,125],"questions,":[61],"inefficient":[64],"easily":[66],"leads":[67],"confusing":[69],"questions.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74,110],"improve":[75],"MRC-based":[78],"model":[81],"through":[82,141],"diverse":[83],"answering.":[85],"First,":[86],"diversity":[88],"mechanism":[91],"introduced":[93],"detect":[95],"entity":[96,129],"spans":[97],"two":[99],"selection":[101],"strategies":[102],"are":[103,133],"designed":[104],"integrate":[106],"different":[107],"answers.":[108],"Then,":[109],"propose":[111],"predict":[113],"subset":[115],"potential":[117],"relations":[118],"filter":[120],"out":[121],"irrelevant":[122],"ones":[123],"questions":[126],"effectively.":[127],"Finally,":[128],"extractions":[132],"integrated":[134],"in":[135],"end-to-end":[137],"way":[138],"optimized":[140],"joint":[142],"learning.":[143],"Experiment":[144],"results":[145],"show":[146],"that":[147],"proposed":[149],"method":[150],"significantly":[151],"outperforms":[152],"baseline":[153],"models,":[154],"improves":[156],"F1":[159],"62.1%":[161],"(+1.9%)":[162],"ACE05":[164],"71.9%":[166],"(+3.0%)":[167],"CoNLL04.":[169],"Our":[170],"implementation":[171],"available":[173],"at":[174],"https://github.com/TanyaZhao/MRC4ERE.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
