{"id":"https://openalex.org/W2295152923","doi":"https://doi.org/10.1109/taslp.2015.2497148","title":"Joint Argument Inference in Chinese Event Extraction with Argument Consistency and Event Relevance","display_name":"Joint Argument Inference in Chinese Event Extraction with Argument Consistency and Event Relevance","publication_year":2015,"publication_date":"2015-11-02","ids":{"openalex":"https://openalex.org/W2295152923","doi":"https://doi.org/10.1109/taslp.2015.2497148","mag":"2295152923"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2015.2497148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2015.2497148","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100695549","display_name":"Peifeng Li","orcid":"https://orcid.org/0000-0003-4850-3128"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peifeng Li","raw_affiliation_strings":["Soochow University, Suzhou, Jiangsu, CN"],"affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, Jiangsu, CN","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012794465","display_name":"Guodong Zhou","orcid":"https://orcid.org/0000-0002-7887-5099"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guodong Zhou","raw_affiliation_strings":["Soochow University, Suzhou, Jiangsu, CN"],"affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, Jiangsu, CN","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100695549"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.4314,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78089716,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"24","issue":"4","first_page":"612","last_page":"622"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","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":0.9926999807357788,"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/argument","display_name":"Argument (complex analysis)","score":0.8432995676994324},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6706086993217468},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6443855166435242},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6353859305381775},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5218906998634338},{"id":"https://openalex.org/keywords/coreference","display_name":"Coreference","score":0.5166173577308655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45709341764450073},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4569639563560486},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4416264593601227},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4362577795982361},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.09585809707641602},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.07517451047897339}],"concepts":[{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.8432995676994324},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6706086993217468},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6443855166435242},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6353859305381775},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5218906998634338},{"id":"https://openalex.org/C28076734","wikidata":"https://www.wikidata.org/wiki/Q63087","display_name":"Coreference","level":3,"score":0.5166173577308655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45709341764450073},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4569639563560486},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4416264593601227},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4362577795982361},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.09585809707641602},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.07517451047897339},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2015.2497148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2015.2497148","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5182775224","display_name":null,"funder_award_id":"61331011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8535532463","display_name":null,"funder_award_id":"61472265","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W16142220","https://openalex.org/W157776793","https://openalex.org/W169290101","https://openalex.org/W752825483","https://openalex.org/W1591840823","https://openalex.org/W1607432077","https://openalex.org/W1877040722","https://openalex.org/W1898214464","https://openalex.org/W1968385461","https://openalex.org/W2013842895","https://openalex.org/W2038037963","https://openalex.org/W2040172363","https://openalex.org/W2071968392","https://openalex.org/W2072628044","https://openalex.org/W2098844768","https://openalex.org/W2103729963","https://openalex.org/W2108743083","https://openalex.org/W2115557995","https://openalex.org/W2118928552","https://openalex.org/W2124634352","https://openalex.org/W2124934171","https://openalex.org/W2127626780","https://openalex.org/W2128364334","https://openalex.org/W2130714105","https://openalex.org/W2134486566","https://openalex.org/W2139813029","https://openalex.org/W2146313271","https://openalex.org/W2165516035","https://openalex.org/W2167439141","https://openalex.org/W2182946785","https://openalex.org/W2185615741","https://openalex.org/W2211728022","https://openalex.org/W2251532181","https://openalex.org/W2403680433","https://openalex.org/W4254061045","https://openalex.org/W4285719527","https://openalex.org/W6600683571","https://openalex.org/W6606440923","https://openalex.org/W6607042197","https://openalex.org/W6621993037","https://openalex.org/W6639278583","https://openalex.org/W6639642803","https://openalex.org/W6674886619","https://openalex.org/W6675412204","https://openalex.org/W6675881536","https://openalex.org/W6677449212","https://openalex.org/W6677780209","https://openalex.org/W6678402113","https://openalex.org/W6678794661","https://openalex.org/W6679064556","https://openalex.org/W6679158365","https://openalex.org/W6679358329","https://openalex.org/W6681536136","https://openalex.org/W6684169581","https://openalex.org/W6684315323","https://openalex.org/W6686108195","https://openalex.org/W6686545002","https://openalex.org/W6687973633","https://openalex.org/W6691137783","https://openalex.org/W6713419435"],"related_works":["https://openalex.org/W2139373276","https://openalex.org/W1509033667","https://openalex.org/W2227889443","https://openalex.org/W4385749782","https://openalex.org/W3167631113","https://openalex.org/W2145164276","https://openalex.org/W2004630825","https://openalex.org/W4243579786","https://openalex.org/W2498065289","https://openalex.org/W4323929292"],"abstract_inverted_index":{"Event":[0],"extraction":[1,18,46],"in":[2,32,47,64,86,115],"Chinese":[3,21,130],"suffers":[4],"greatly":[5,39],"from":[6,67],"the":[7,15,41,127,133],"frequent":[8],"missing":[9,62],"of":[10,14,27,44,78,126,135],"arguments.":[11],"Statistical":[12],"analysis":[13],"automatic":[16],"content":[17],"(ACE)":[19],"2005":[20,129],"corpus":[22,131],"shows":[23],"that":[24],"nearly":[25],"55%":[26],"arguments":[28,63],"do":[29],"not":[30],"occur":[31],"their":[33],"corresponding":[34],"event":[35,45,65,101],"mentions.":[36],"This":[37,50],"problem":[38],"hinders":[40],"wide":[42],"deployment":[43],"real":[48],"applications.":[49],"paper":[51],"proposes":[52],"a":[53,68,143],"novel":[54],"joint":[55,137],"argument":[56,79,84,113,138],"inference":[57,139],"model":[58,74,97,140],"to":[59,81,110,142],"recover":[60],"those":[61],"mentions":[66],"semantic":[69],"perspective.":[70],"In":[71],"particular,":[72],"this":[73,96],"employs":[75],"various":[76,116],"types":[77],"consistencies":[80],"reveal":[82],"intra-event":[83],"semantics":[85,114],"multiple":[87],"dimensions,":[88],"such":[89,104,118],"as":[90,105,119],"argument-argument,":[91],"argument-role":[92],"and":[93,108,122],"argument-trigger.":[94],"Moreover,":[95],"explores":[98],"several":[99],"linguistic-driven":[100],"relevance":[102],"phenomena,":[103],"Coreference,":[106],"Sequence,":[107],"Parallel,":[109],"unveil":[111],"inter-event":[112],"layers,":[117],"sentence,":[120],"discourse,":[121],"document.":[123],"An":[124],"evaluation":[125],"ACE":[128],"justifies":[132],"effectiveness":[134],"our":[136],"compared":[141],"state-of-the-art":[144],"baseline.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
