{"id":"https://openalex.org/W4285306609","doi":"https://doi.org/10.18653/v1/2022.acl-long.59","title":"De-Bias for Generative Extraction in Unified NER Task","display_name":"De-Bias for Generative Extraction in Unified NER Task","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285306609","doi":"https://doi.org/10.18653/v1/2022.acl-long.59"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.acl-long.59","pdf_url":"https://aclanthology.org/2022.acl-long.59.pdf","source":{"id":"https://openalex.org/S4363608652","display_name":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2022.acl-long.59.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100328838","display_name":"Shuai Zhang","orcid":"https://orcid.org/0000-0001-8502-2927"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Zhang","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004615610","display_name":"Yongliang Shen","orcid":"https://orcid.org/0000-0003-0975-3554"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongliang Shen","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060694956","display_name":"Zeqi Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeqi Tan","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101615578","display_name":"Yiquan Wu","orcid":"https://orcid.org/0000-0002-3556-0898"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiquan Wu","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026310569","display_name":"Weiming L\u00fc","orcid":"https://orcid.org/0000-0003-1561-2467"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Lu","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University","institution_ids":["https://openalex.org/I168879160"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.207,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":36,"citation_normalized_percentile":{"value":0.999889,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9996,"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":0.9996,"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":0.9949,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9701,"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/generative-model","display_name":"Generative model","score":0.5651745},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named Entity Recognition","score":0.50359625}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7816443},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7416956},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.660927},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6168141},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5651745},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5337143},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.52723426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5251783},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.50359625},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4950389},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33409005},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06449422},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/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}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.acl-long.59","pdf_url":"https://aclanthology.org/2022.acl-long.59.pdf","source":{"id":"https://openalex.org/S4363608652","display_name":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.acl-long.59","pdf_url":"https://aclanthology.org/2022.acl-long.59.pdf","source":{"id":"https://openalex.org/S4363608652","display_name":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.46,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":52,"referenced_works":["https://openalex.org/W1573258796","https://openalex.org/W1940872118","https://openalex.org/W2004763266","https://openalex.org/W2022113049","https://openalex.org/W2103076621","https://openalex.org/W2131546905","https://openalex.org/W2141099517","https://openalex.org/W2148385623","https://openalex.org/W2155069789","https://openalex.org/W2163107094","https://openalex.org/W2250710764","https://openalex.org/W2296283641","https://openalex.org/W2407338347","https://openalex.org/W2486285194","https://openalex.org/W2573840943","https://openalex.org/W2612773933","https://openalex.org/W2740006839","https://openalex.org/W2802788932","https://openalex.org/W2803609931","https://openalex.org/W2804221886","https://openalex.org/W2891602716","https://openalex.org/W2908510526","https://openalex.org/W2935052563","https://openalex.org/W2946558277","https://openalex.org/W2952087486","https://openalex.org/W2952230511","https://openalex.org/W2952594430","https://openalex.org/W2962739339","https://openalex.org/W2962833164","https://openalex.org/W2963568202","https://openalex.org/W2963625095","https://openalex.org/W2964167098","https://openalex.org/W2971064981","https://openalex.org/W2983180560","https://openalex.org/W3017819929","https://openalex.org/W3023337184","https://openalex.org/W3034379414","https://openalex.org/W3034744126","https://openalex.org/W3035375600","https://openalex.org/W3035625205","https://openalex.org/W3090015871","https://openalex.org/W3101188882","https://openalex.org/W3102603416","https://openalex.org/W3104415840","https://openalex.org/W3104692733","https://openalex.org/W3105928338","https://openalex.org/W3121525843","https://openalex.org/W3156977337","https://openalex.org/W3175225269","https://openalex.org/W3176680950","https://openalex.org/W3187731984","https://openalex.org/W4288089799"],"related_works":["https://openalex.org/W4385572368","https://openalex.org/W4285197708","https://openalex.org/W4200223488","https://openalex.org/W3193140313","https://openalex.org/W3171566221","https://openalex.org/W3115095335","https://openalex.org/W3019278637","https://openalex.org/W2773616286","https://openalex.org/W159132833","https://openalex.org/W1573537589"],"abstract_inverted_index":{"Named":[0],"entity":[1],"recognition":[2],"(NER)":[3],"is":[4,63,70],"a":[5,15,98],"fundamental":[6],"task":[7],"to":[8,54,65,81,104,122,128],"recognize":[9],"specific":[10],"types":[11],"of":[12,131,143],"entities":[13,22],"from":[14,97],"given":[16],"sentence.":[17],"Depending":[18],"on":[19],"how":[20],"the":[21,25,43,47,60,74,78,82,90,94,124,129,141,144],"appear":[23],"in":[24,93,148],"sentence,":[26],"it":[27],"can":[28,50,139],"be":[29,51],"divided":[30],"into":[31],"three":[32,56],"subtasks,":[33],"namely,":[34],"Flat":[35],"NER,":[36,38,66],"Nested":[37],"and":[39,101,109,116],"Discontinuous":[40],"NER.":[41],"Among":[42],"existing":[44],"approaches,":[45],"only":[46],"generative":[48,61,145],"model":[49,62,79,147],"uniformly":[52],"adapted":[53],"these":[55],"subtasks.":[57],"However,":[58],"when":[59],"applied":[64],"its":[67],"optimization":[68],"objective":[69],"not":[71],"consistent":[72],"with":[73],"task,":[75],"which":[76],"makes":[77],"vulnerable":[80],"incorrect":[83,91],"biases.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88,113],"analyze":[89],"biases":[92],"generation":[95],"process":[96],"causality":[99],"perspective":[100],"attribute":[102],"them":[103],"two":[105],"confounders:":[106],"pre-context":[107],"confounder":[108],"entity-order":[110],"confounder.":[111],"Furthermore,":[112],"design":[114],"Intra-":[115],"Inter-entity":[117],"Deconfounding":[118],"Data":[119],"Augmentation":[120],"methods":[121],"eliminate":[123],"above":[125],"confounders":[126],"according":[127],"theory":[130],"backdoor":[132],"adjustment.":[133],"Experiments":[134],"show":[135],"that":[136],"our":[137],"method":[138],"improve":[140],"performance":[142],"NER":[146],"various":[149],"datasets.":[150]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4285306609","counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":5}],"updated_date":"2025-04-18T20:41:27.468829","created_date":"2022-07-14"}