{"id":"https://openalex.org/W2949922292","doi":"https://doi.org/10.18653/v1/p19-1129","title":"Entity-Relation Extraction as Multi-Turn Question Answering","display_name":"Entity-Relation Extraction as Multi-Turn Question Answering","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2949922292","doi":"https://doi.org/10.18653/v1/p19-1129","mag":"2949922292"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1129","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1129","pdf_url":"https://www.aclweb.org/anthology/P19-1129.pdf","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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1129.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100651417","display_name":"Xiaoya Li","orcid":"https://orcid.org/0009-0008-5742-4855"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoya Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053347296","display_name":"Fan Yin","orcid":"https://orcid.org/0000-0002-8028-2217"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan Yin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076728540","display_name":"Zijun Sun","orcid":"https://orcid.org/0000-0001-5386-5495"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zijun Sun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103989843","display_name":"Xiayu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiayu Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109463284","display_name":"Arianna Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arianna Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103911469","display_name":"Duo Chai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duo Chai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034626719","display_name":"Mingxin Zhou","orcid":"https://orcid.org/0000-0002-1748-7180"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mingxin Zhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100758099","display_name":"Jiwei Li","orcid":"https://orcid.org/0000-0003-3655-7313"},"institutions":[{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]},{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]},{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["CN","FR","US"],"is_corresponding":true,"raw_author_name":"Jiwei Li","raw_affiliation_strings":["Computer Center, Peking University  Computer Science Department, Stanford University  Shannon.AI","School of Information, Renmin University of China","\u2666 Computer Center, Peking University \u2665 Computer Science Department, Stanford University \u2660 Shannon.AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Center, Peking University  Computer Science Department, Stanford University  Shannon.AI","institution_ids":["https://openalex.org/I111483173"]},{"raw_affiliation_string":"School of Information, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"\u2666 Computer Center, Peking University \u2665 Computer Science Department, Stanford University \u2660 Shannon.AI","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210156583","https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100758099"],"corresponding_institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570","https://openalex.org/I4210156583","https://openalex.org/I78988378","https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":21.3219,"has_fulltext":true,"cited_by_count":352,"citation_normalized_percentile":{"value":0.99583249,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1340","last_page":"1350"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9829000234603882,"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/computer-science","display_name":"Computer science","score":0.860566258430481},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.8215513229370117},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.7630220651626587},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6176619529724121},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6175107955932617},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6113176345825195},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5845057964324951},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5560488104820251},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.53554368019104},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5142881274223328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5134168863296509},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.4904429614543915},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.43497195839881897},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.4341164231300354},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4315757751464844},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3148062527179718},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.12175783514976501}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.860566258430481},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8215513229370117},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.7630220651626587},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6176619529724121},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6175107955932617},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6113176345825195},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5845057964324951},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5560488104820251},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.53554368019104},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5142881274223328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5134168863296509},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.4904429614543915},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43497195839881897},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.4341164231300354},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4315757751464844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3148062527179718},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.12175783514976501},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1129","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1129","pdf_url":"https://www.aclweb.org/anthology/P19-1129.pdf","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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1129","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1129","pdf_url":"https://www.aclweb.org/anthology/P19-1129.pdf","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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2949922292.pdf","grobid_xml":"https://content.openalex.org/works/W2949922292.grobid-xml"},"referenced_works_count":68,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1566346388","https://openalex.org/W1866795174","https://openalex.org/W1940872118","https://openalex.org/W1996787131","https://openalex.org/W2047192163","https://openalex.org/W2077054525","https://openalex.org/W2099118758","https://openalex.org/W2115090890","https://openalex.org/W2115834228","https://openalex.org/W2119717200","https://openalex.org/W2132516856","https://openalex.org/W2133439966","https://openalex.org/W2134033474","https://openalex.org/W2145339207","https://openalex.org/W2147880316","https://openalex.org/W2162590473","https://openalex.org/W2250861254","https://openalex.org/W2251091211","https://openalex.org/W2296073425","https://openalex.org/W2465041517","https://openalex.org/W2513378248","https://openalex.org/W2515462165","https://openalex.org/W2516930406","https://openalex.org/W2521709538","https://openalex.org/W2551396370","https://openalex.org/W2552110825","https://openalex.org/W2559038528","https://openalex.org/W2566011400","https://openalex.org/W2578454709","https://openalex.org/W2579486552","https://openalex.org/W2587809655","https://openalex.org/W2609826708","https://openalex.org/W2625541525","https://openalex.org/W2740747242","https://openalex.org/W2741956709","https://openalex.org/W2750557179","https://openalex.org/W2759056771","https://openalex.org/W2766371743","https://openalex.org/W2769395616","https://openalex.org/W2798734500","https://openalex.org/W2798858969","https://openalex.org/W2809324505","https://openalex.org/W2891935547","https://openalex.org/W2896457183","https://openalex.org/W2950314731","https://openalex.org/W2962739339","https://openalex.org/W2962881743","https://openalex.org/W2962902328","https://openalex.org/W2962913831","https://openalex.org/W2963195889","https://openalex.org/W2963339397","https://openalex.org/W2963341956","https://openalex.org/W2963355447","https://openalex.org/W2963403868","https://openalex.org/W2963571341","https://openalex.org/W2963748441","https://openalex.org/W2963788376","https://openalex.org/W2963797754","https://openalex.org/W2963863909","https://openalex.org/W2963912690","https://openalex.org/W2963997908","https://openalex.org/W2964121744","https://openalex.org/W2964167098","https://openalex.org/W4285719527","https://openalex.org/W4293350112","https://openalex.org/W4295253143","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2352298027","https://openalex.org/W4319940250","https://openalex.org/W842810586","https://openalex.org/W2167202928","https://openalex.org/W2092919065","https://openalex.org/W1984061923","https://openalex.org/W4236762297","https://openalex.org/W3138801416","https://openalex.org/W173870552","https://openalex.org/W2369351710"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,63],"propose":[4],"a":[5,19,70],"new":[6],"paradigm":[7],"for":[8,59],"the":[9,16,25,34,41,53,60,86],"task":[10,17,35],"of":[11,27,36,73],"entity-relation":[12],"extraction.":[13],"We":[14],"cast":[15],"as":[18],"multi-turn":[20,44],"question":[21,54],"answering":[22],"problem,":[23],"i.e.,":[24],"extraction":[26],"entities":[28],"and":[29,77,79],"relations":[30],"is":[31],"transformed":[32],"to":[33,65,84],"identifying":[37],"answer":[38],"spans":[39],"from":[40],"context.":[42],"This":[43],"QA":[45,68],"formalization":[46],"comes":[47],"with":[48],"several":[49],"key":[50],"advantages:":[51],"firstly,":[52],"query":[55],"encodes":[56],"important":[57],"information":[58],"entity/relation":[61],"class":[62],"want":[64],"identify;":[66],"secondly,":[67],"provides":[69],"natural":[71],"way":[72],"jointly":[74],"modeling":[75],"entity":[76],"relation;":[78],"thirdly,":[80],"it":[81],"allows":[82],"us":[83],"exploit":[85],"well":[87],"developed":[88],"machine":[89],"reading":[90],"comprehension":[91],"(MRC)":[92],"models.":[93]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":58},{"year":2023,"cited_by_count":67},{"year":2022,"cited_by_count":63},{"year":2021,"cited_by_count":84},{"year":2020,"cited_by_count":41},{"year":2019,"cited_by_count":7}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}