{"id":"https://openalex.org/W2799167615","doi":"https://doi.org/10.18653/v1/p18-1045","title":"Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures","display_name":"Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2799167615","doi":"https://doi.org/10.18653/v1/p18-1045","mag":"2799167615"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-1045","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1045","pdf_url":"https://www.aclweb.org/anthology/P18-1045.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","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/P18-1045.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113067484","display_name":"Prafulla Kumar Choubey","orcid":null},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prafulla Kumar Choubey","raw_affiliation_strings":["Department of Computer Science and Engineering Texas A&M University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering Texas A&M University","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101688218","display_name":"Ruihong Huang","orcid":"https://orcid.org/0000-0002-4639-7766"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruihong Huang","raw_affiliation_strings":["Department of Computer Science and Engineering Texas A&M University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering Texas A&M University","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":2.1504,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.91086302,"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":"485","last_page":"495"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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":0.998199999332428,"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":0.9972273707389832},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.791934609413147},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6601449847221375},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5756217837333679},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5621236562728882},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5575413703918457},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.498058557510376}],"concepts":[{"id":"https://openalex.org/C28076734","wikidata":"https://www.wikidata.org/wiki/Q63087","display_name":"Coreference","level":3,"score":0.9972273707389832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.791934609413147},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6601449847221375},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5756217837333679},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5621236562728882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5575413703918457},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.498058557510376},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p18-1045","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1045","pdf_url":"https://www.aclweb.org/anthology/P18-1045.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p18-1045","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1045","pdf_url":"https://www.aclweb.org/anthology/P18-1045.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8937052439","display_name":"CRII: RI: Subevent Acquisition and Analysis","funder_award_id":"1755943","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2799167615.pdf","grobid_xml":"https://content.openalex.org/works/W2799167615.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W60009487","https://openalex.org/W746041417","https://openalex.org/W1965693266","https://openalex.org/W2010581447","https://openalex.org/W2014394530","https://openalex.org/W2072628044","https://openalex.org/W2096335387","https://openalex.org/W2098345921","https://openalex.org/W2101234009","https://openalex.org/W2112220279","https://openalex.org/W2123442489","https://openalex.org/W2124741472","https://openalex.org/W2130031580","https://openalex.org/W2147218300","https://openalex.org/W2147706904","https://openalex.org/W2157944021","https://openalex.org/W2160583993","https://openalex.org/W2180160918","https://openalex.org/W2250487771","https://openalex.org/W2250539671","https://openalex.org/W2251552857","https://openalex.org/W2251628379","https://openalex.org/W2252089544","https://openalex.org/W2252123151","https://openalex.org/W2518186251","https://openalex.org/W2563336465","https://openalex.org/W2572433848","https://openalex.org/W2609608256","https://openalex.org/W2741719406","https://openalex.org/W2803693270","https://openalex.org/W2806332557","https://openalex.org/W2807441601","https://openalex.org/W2916277162","https://openalex.org/W2917198466","https://openalex.org/W2962751953","https://openalex.org/W2962769558","https://openalex.org/W2963167649","https://openalex.org/W2963902285","https://openalex.org/W2964222246"],"related_works":["https://openalex.org/W3041549465","https://openalex.org/W2380610138","https://openalex.org/W3171444480","https://openalex.org/W4221148125","https://openalex.org/W3212412177","https://openalex.org/W4385570846","https://openalex.org/W4206648670","https://openalex.org/W1594011529","https://openalex.org/W2529509480","https://openalex.org/W2339319059"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,37,60,72],"novel":[4],"approach":[5],"for":[6,65],"event":[7,14,34,46,69,91],"coreference":[8,15,62,92],"resolution":[9,93],"that":[10,83],"models":[11],"correlations":[12,30],"between":[13,31],"chains":[16,35,70],"and":[17,50,53,79],"document":[18,38],"topical":[19],"structures":[20,87],"through":[21],"an":[22],"Integer":[23],"Linear":[24],"Programming":[25],"formulation.":[26],"We":[27],"explicitly":[28],"model":[29],"the":[32,86],"main":[33],"of":[36,85],"with":[39,56],"topic":[40],"transition":[41],"sentences,":[42],"inter-coreference":[43],"chain":[44],"correlations,":[45],"mention":[47],"distributional":[48],"characteristics":[49],"sub-event":[51],"structure,":[52],"use":[54],"them":[55],"scores":[57],"obtained":[58],"from":[59],"local":[61],"relation":[63],"classifier":[64],"jointly":[66],"resolving":[67],"multiple":[68],"in":[71],"document.":[73],"Our":[74],"experiments":[75],"across":[76],"KBP":[77],"2016":[78],"2017":[80],"datasets":[81],"suggest":[82],"each":[84],"contribute":[88],"to":[89],"improving":[90],"performance.":[94]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
