{"id":"https://openalex.org/W4377371631","doi":"https://doi.org/10.48550/arxiv.2305.11498","title":"Recouple Event Field via Probabilistic Bias for Event Extraction","display_name":"Recouple Event Field via Probabilistic Bias for Event Extraction","publication_year":2023,"publication_date":"2023-05-19","ids":{"openalex":"https://openalex.org/W4377371631","doi":"https://doi.org/10.48550/arxiv.2305.11498"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2305.11498","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.11498","pdf_url":"https://arxiv.org/pdf/2305.11498","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2305.11498","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100526509","display_name":"Xingyu Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bai, Xingyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074532565","display_name":"Taiqiang Wu","orcid":"https://orcid.org/0000-0002-3664-3513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Taiqiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101839615","display_name":"Han Guo","orcid":"https://orcid.org/0000-0001-7535-5621"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Han","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631152","display_name":"Zhe Zhao","orcid":"https://orcid.org/0000-0003-4189-3258"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Zhe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100715830","display_name":"Xuefeng Yang","orcid":"https://orcid.org/0000-0002-3832-2422"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xuefeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100446476","display_name":"Jiayi Li","orcid":"https://orcid.org/0000-0002-1934-2129"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jiayi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668786","display_name":"Weijie Liu","orcid":"https://orcid.org/0000-0002-8023-9913"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Weijie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071290194","display_name":"Qi Ju","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ju, Qi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100308278","display_name":"Weigang Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Weigang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5020953714","display_name":"Yujiu Yang","orcid":"https://orcid.org/0000-0002-6427-1024"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yujiu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5100526509"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9987999796867371,"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":0.9894999861717224,"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.8027465343475342},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7927155494689941},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6145627498626709},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.605573296546936},{"id":"https://openalex.org/keywords/argument","display_name":"Argument (complex analysis)","score":0.5216981768608093},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5004467964172363},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.48470258712768555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4598255157470703},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36642390489578247},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3334173858165741},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22781610488891602},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0678655207157135}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.8027465343475342},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7927155494689941},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6145627498626709},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.605573296546936},{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.5216981768608093},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5004467964172363},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.48470258712768555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4598255157470703},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36642390489578247},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3334173858165741},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22781610488891602},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0678655207157135},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2305.11498","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.11498","pdf_url":"https://arxiv.org/pdf/2305.11498","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2305.11498","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2305.11498","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.11498","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.11498","pdf_url":"https://arxiv.org/pdf/2305.11498","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3178363158","display_name":null,"funder_award_id":"202008","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5517038434","display_name":null,"funder_award_id":"2020YFB","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G792937614","display_name":null,"funder_award_id":"1708200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8643918816","display_name":null,"funder_award_id":"2020YFB1708200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4377371631.pdf","grobid_xml":"https://content.openalex.org/works/W4377371631.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3008380943","https://openalex.org/W3162204513","https://openalex.org/W2115206405","https://openalex.org/W4387718383","https://openalex.org/W1528986568","https://openalex.org/W2500746363","https://openalex.org/W2062799661","https://openalex.org/W2371138613","https://openalex.org/W2804199312","https://openalex.org/W2048963458"],"abstract_inverted_index":{"Event":[0,49],"Extraction":[1],"(EE),":[2],"aiming":[3],"to":[4,64,94],"identify":[5],"and":[6,10,100,113],"classify":[7],"event":[8,13,37,59,67],"triggers":[9],"arguments":[11],"from":[12,17,69],"mentions,":[14],"has":[15],"benefited":[16],"pre-trained":[18],"language":[19],"models":[20],"(PLMs).":[21],"However,":[22],"existing":[23],"PLM-based":[24],"methods":[25],"ignore":[26],"the":[27,57,66,77,91,96,111],"information":[28,104],"of":[29,76,90,115],"trigger/argument":[30],"fields,":[31],"which":[32],"is":[33],"crucial":[34],"for":[35],"understanding":[36],"schemas.":[38],"To":[39],"this":[40],"end,":[41],"we":[42,54,82],"propose":[43],"a":[44],"Probabilistic":[45],"reCoupling":[46],"model":[47,56],"enhanced":[48],"extraction":[50],"framework":[51],"(ProCE).":[52],"Specifically,":[53],"first":[55],"syntactic-related":[58],"fields":[60,68,89],"as":[61],"probabilistic":[62,84],"biases,":[63],"clarify":[65],"ambiguous":[70],"entanglement.":[71],"Furthermore,":[72],"considering":[73],"multiple":[74,88],"occurrences":[75],"same":[78,92],"triggers/arguments":[79],"in":[80],"EE,":[81],"explore":[83],"interaction":[85],"strategies":[86],"among":[87],"triggers/arguments,":[93],"recouple":[95],"corresponding":[97],"clarified":[98],"distributions":[99],"capture":[101],"more":[102],"latent":[103],"fields.":[105],"Experiments":[106],"on":[107],"EE":[108],"datasets":[109],"demonstrate":[110],"effectiveness":[112],"generalization":[114],"our":[116],"proposed":[117],"approach.":[118]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
