{"id":"https://openalex.org/W2899501643","doi":"https://doi.org/10.18653/v1/p19-1386","title":"The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution","display_name":"The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2899501643","doi":"https://doi.org/10.18653/v1/p19-1386","mag":"2899501643"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1386","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1386","pdf_url":"https://www.aclweb.org/anthology/P19-1386.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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1386.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064694944","display_name":"Ali Emami","orcid":"https://orcid.org/0000-0003-0898-7770"},"institutions":[{"id":"https://openalex.org/I4210155582","display_name":"Centre Universitaire de Mila","ror":"https://ror.org/05s3cw058","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210155582"]},{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA","DZ"],"is_corresponding":false,"raw_author_name":"Ali Emami","raw_affiliation_strings":["School of Computer Science, Mila/McGill University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Mila/McGill University","institution_ids":["https://openalex.org/I4210155582","https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044824672","display_name":"Paul Trichelair","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155582","display_name":"Centre Universitaire de Mila","ror":"https://ror.org/05s3cw058","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210155582"]},{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA","DZ"],"is_corresponding":false,"raw_author_name":"Paul Trichelair","raw_affiliation_strings":["School of Computer Science, Mila/McGill University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Mila/McGill University","institution_ids":["https://openalex.org/I4210155582","https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072931308","display_name":"Adam Trischler","orcid":"https://orcid.org/0000-0003-1118-8224"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I4402554038","display_name":"Microsoft Research Montr\u00e9al (Canada)","ror":"https://ror.org/05xdft911","country_code":null,"type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4402554038"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adam Trischler","raw_affiliation_strings":["Microsoft Research Montreal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Montreal","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I4402554038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103376786","display_name":"Kaheer Suleman","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I4402554038","display_name":"Microsoft Research Montr\u00e9al (Canada)","ror":"https://ror.org/05xdft911","country_code":null,"type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4402554038"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kaheer Suleman","raw_affiliation_strings":["Microsoft Research Montreal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Montreal","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I4402554038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088078468","display_name":"Hannes Schulz","orcid":"https://orcid.org/0000-0001-6408-9794"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I4402554038","display_name":"Microsoft Research Montr\u00e9al (Canada)","ror":"https://ror.org/05xdft911","country_code":null,"type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4402554038"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hannes Schulz","raw_affiliation_strings":["Microsoft Research Montreal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Montreal","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I4402554038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050801868","display_name":"Jackie Chi Kit Cheung","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155582","display_name":"Centre Universitaire de Mila","ror":"https://ror.org/05s3cw058","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210155582"]},{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA","DZ"],"is_corresponding":false,"raw_author_name":"Jackie Chi Kit Cheung","raw_affiliation_strings":["School of Computer Science, Mila/McGill University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Mila/McGill University","institution_ids":["https://openalex.org/I4210155582","https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.6274,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.95719591,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3952","last_page":"3961"},"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":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/T13629","display_name":"Text Readability and Simplification","score":0.9986000061035156,"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/coreference","display_name":"Coreference","score":0.9853847026824951},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8220785856246948},{"id":"https://openalex.org/keywords/antecedent","display_name":"Antecedent (behavioral psychology)","score":0.7944046258926392},{"id":"https://openalex.org/keywords/anaphora","display_name":"Anaphora (linguistics)","score":0.7667138576507568},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.703359067440033},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6797035932540894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6692869663238525},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6542510390281677},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6335703730583191},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.57503741979599},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5398684144020081},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.18556275963783264},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08176812529563904}],"concepts":[{"id":"https://openalex.org/C28076734","wikidata":"https://www.wikidata.org/wiki/Q63087","display_name":"Coreference","level":3,"score":0.9853847026824951},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8220785856246948},{"id":"https://openalex.org/C2781256819","wikidata":"https://www.wikidata.org/wiki/Q16828835","display_name":"Antecedent (behavioral psychology)","level":2,"score":0.7944046258926392},{"id":"https://openalex.org/C2781449363","wikidata":"https://www.wikidata.org/wiki/Q156751","display_name":"Anaphora (linguistics)","level":3,"score":0.7667138576507568},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.703359067440033},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6797035932540894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6692869663238525},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6542510390281677},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6335703730583191},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.57503741979599},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5398684144020081},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.18556275963783264},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08176812529563904},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C138496976","wikidata":"https://www.wikidata.org/wiki/Q175002","display_name":"Developmental psychology","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1386","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1386","pdf_url":"https://www.aclweb.org/anthology/P19-1386.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/p19-1386","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1386","pdf_url":"https://www.aclweb.org/anthology/P19-1386.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/5","score":0.6299999952316284,"display_name":"Gender equality"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"},{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1495981708","https://openalex.org/W1599016936","https://openalex.org/W1752492850","https://openalex.org/W2068580143","https://openalex.org/W2068882115","https://openalex.org/W2099115159","https://openalex.org/W2101268022","https://openalex.org/W2109286446","https://openalex.org/W2124700572","https://openalex.org/W2129657639","https://openalex.org/W2133236963","https://openalex.org/W2155069789","https://openalex.org/W2167140078","https://openalex.org/W2180160918","https://openalex.org/W2251035762","https://openalex.org/W2252031764","https://openalex.org/W2291406294","https://openalex.org/W2296266385","https://openalex.org/W2303427901","https://openalex.org/W2340581863","https://openalex.org/W2407338347","https://openalex.org/W2805206884","https://openalex.org/W2896457183","https://openalex.org/W2898785098","https://openalex.org/W2920114910","https://openalex.org/W2953149585","https://openalex.org/W2963087868","https://openalex.org/W2963167649","https://openalex.org/W2963341956","https://openalex.org/W2963457723","https://openalex.org/W2963526187","https://openalex.org/W2963695529","https://openalex.org/W2964222246","https://openalex.org/W3023431232","https://openalex.org/W4253336001","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3157556506","https://openalex.org/W2251064706","https://openalex.org/W1539566881","https://openalex.org/W4281770883","https://openalex.org/W2361342447","https://openalex.org/W2045494691","https://openalex.org/W4387184536","https://openalex.org/W2339319059","https://openalex.org/W2884082915","https://openalex.org/W3096231636"],"abstract_inverted_index":{"We":[0,49,70,125],"introduce":[1],"a":[2,51,123,132],"new":[3],"benchmark":[4],"for":[5],"coreference":[6,19,74,168],"resolution":[7,20],"and":[8,15,30,39,68],"NLI,":[9],"KNOWREF,":[10],"that":[11,72,102,147],"targets":[12],"common-sense":[13],"understanding":[14],"world":[16],"knowledge.":[17],"Previous":[18],"tasks":[21,155],"can":[22],"largely":[23],"be":[24],"solved":[25],"by":[26],"exploiting":[27],"the":[28,33,43,85,114,166],"number":[29,117],"gender":[31,115],"of":[32,45,53,118],"antecedents,":[34],"or":[35,79,116],"have":[36],"been":[37],"handcrafted":[38],"do":[40],"not":[41],"reflect":[42],"diversity":[44],"naturally":[46],"occurring":[47],"text.":[48],"present":[50],"corpus":[52],"over":[54],"8,000":[55],"annotated":[56],"text":[57],"passages":[58],"with":[59],"ambiguous":[60],"pronominal":[61],"anaphora.":[62],"These":[63],"instances":[64],"are":[65],"both":[66],"challenging":[67],"realistic.":[69],"show":[71,100,146],"various":[73],"systems,":[75],"whether":[76],"rule-based,":[77],"feature-rich,":[78],"neural,":[80],"perform":[81],"significantly":[82],"worse":[83],"on":[84,113,153,165],"task":[86],"than":[87],"humans,":[88],"who":[89],"display":[90],"high":[91],"interannotator":[92],"agreement.":[93],"To":[94],"explain":[95],"this":[96,140],"performance":[97],"gap,":[98],"we":[99,145,158],"empirically":[101],"state-ofthe":[103],"art":[104],"models":[105],"often":[106],"fail":[107],"to":[108,121,130,138,161],"capture":[109],"context,":[110],"instead":[111],"relying":[112],"candidate":[119],"antecedents":[120],"make":[122],"decision.":[124],"then":[126],"use":[127,159],"problem-specific":[128],"insights":[129],"propose":[131],"data-augmentation":[133],"trick":[134],"called":[135],"antecedent":[136,148],"switching":[137,149],"alleviate":[139],"tendency":[141],"in":[142],"models.":[143],"Finally,":[144],"yields":[150],"promising":[151],"results":[152,164],"other":[154],"as":[156],"well:":[157],"it":[160],"achieve":[162],"state-of-the-art":[163],"GAP":[167],"task.":[169]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
