{"id":"https://openalex.org/W2251644265","doi":"https://doi.org/10.3115/v1/d14-1090","title":"Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features","display_name":"Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2251644265","doi":"https://doi.org/10.3115/v1/d14-1090","mag":"2251644265"},"language":"en","primary_location":{"id":"doi:10.3115/v1/d14-1090","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1090","pdf_url":"https://aclanthology.org/D14-1090.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 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/D14-1090.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103421781","display_name":"Deepak Venugopal","orcid":"https://orcid.org/0000-0001-7466-5417"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deepak Venugopal","raw_affiliation_strings":["Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418485","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0002-7099-7905"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Chen","raw_affiliation_strings":["Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038455119","display_name":"Vibhav Gogate","orcid":"https://orcid.org/0000-0002-6459-7358"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vibhav Gogate","raw_affiliation_strings":["Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004305684","display_name":"Vincent Ng","orcid":"https://orcid.org/0000-0002-5114-3883"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vincent Ng","raw_affiliation_strings":["Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Human Language Technology Research Institute University of Texas at Dallas Richardson, TX 75083-0688","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5038455119"],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":67,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"831","last_page":"843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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":0.9957000017166138,"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/computer-science","display_name":"Computer science","score":0.8620277643203735},{"id":"https://openalex.org/keywords/biomedical-text-mining","display_name":"Biomedical text mining","score":0.8295964002609253},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6403049230575562},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.599494993686676},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.49953794479370117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4902699291706085},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.48694074153900146},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4718468189239502},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47096970677375793},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4572993218898773},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3965831398963928},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3414928615093231},{"id":"https://openalex.org/keywords/text-mining","display_name":"Text mining","score":0.12242472171783447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8620277643203735},{"id":"https://openalex.org/C165141518","wikidata":"https://www.wikidata.org/wiki/Q4915126","display_name":"Biomedical text mining","level":3,"score":0.8295964002609253},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6403049230575562},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.599494993686676},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.49953794479370117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4902699291706085},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.48694074153900146},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4718468189239502},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47096970677375793},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4572993218898773},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3965831398963928},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3414928615093231},{"id":"https://openalex.org/C71472368","wikidata":"https://www.wikidata.org/wiki/Q676880","display_name":"Text mining","level":2,"score":0.12242472171783447},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3115/v1/d14-1090","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1090","pdf_url":"https://aclanthology.org/D14-1090.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 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.679.7186","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.679.7186","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.hlt.utdallas.edu/%7Evgogate/papers/emnlp14.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.682.914","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://emnlp2014.org/papers/pdf/EMNLP2014090.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.696.2855","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.2855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D14/D14-1090.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/d14-1090","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1090","pdf_url":"https://aclanthology.org/D14-1090.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 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3622582212","display_name":null,"funder_award_id":"W911NF-08-1","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G3886984593","display_name":null,"funder_award_id":"W911NF-08-1-0242","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G7009995026","display_name":null,"funder_award_id":"W911NF-08-1-0242","funder_id":"https://openalex.org/F4320333591","funder_display_name":"Multidisciplinary University Research Initiative"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2251644265.pdf","grobid_xml":"https://content.openalex.org/works/W2251644265.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W16142220","https://openalex.org/W47392883","https://openalex.org/W76749362","https://openalex.org/W121805954","https://openalex.org/W122290181","https://openalex.org/W136394213","https://openalex.org/W154351976","https://openalex.org/W165790511","https://openalex.org/W752825483","https://openalex.org/W1508671669","https://openalex.org/W1511986666","https://openalex.org/W1535439311","https://openalex.org/W1569098853","https://openalex.org/W1576520375","https://openalex.org/W1585529040","https://openalex.org/W1599188306","https://openalex.org/W1787402258","https://openalex.org/W1877040722","https://openalex.org/W1898214464","https://openalex.org/W1965417459","https://openalex.org/W1965893653","https://openalex.org/W1997945384","https://openalex.org/W2008652694","https://openalex.org/W2017127020","https://openalex.org/W2032566933","https://openalex.org/W2038037963","https://openalex.org/W2072628044","https://openalex.org/W2075655036","https://openalex.org/W2092654472","https://openalex.org/W2098162425","https://openalex.org/W2102563561","https://openalex.org/W2108706252","https://openalex.org/W2108743083","https://openalex.org/W2110408238","https://openalex.org/W2120727810","https://openalex.org/W2122003883","https://openalex.org/W2123661878","https://openalex.org/W2128364334","https://openalex.org/W2134486566","https://openalex.org/W2146313271","https://openalex.org/W2149803936","https://openalex.org/W2155598164","https://openalex.org/W2156909104","https://openalex.org/W2165516035","https://openalex.org/W2165962657","https://openalex.org/W2170953709","https://openalex.org/W2185615741","https://openalex.org/W2211728022","https://openalex.org/W2250259034","https://openalex.org/W2250469303","https://openalex.org/W2250591852","https://openalex.org/W2251108261","https://openalex.org/W2251251652","https://openalex.org/W2251279337","https://openalex.org/W2251814321","https://openalex.org/W2252226131","https://openalex.org/W2429914308","https://openalex.org/W2503079136","https://openalex.org/W2525721411","https://openalex.org/W2916355958","https://openalex.org/W4253741391","https://openalex.org/W4300868862"],"related_works":["https://openalex.org/W2887358545","https://openalex.org/W2090763504","https://openalex.org/W2914463643","https://openalex.org/W148178222","https://openalex.org/W4241083716","https://openalex.org/W3185751515","https://openalex.org/W2104657898","https://openalex.org/W3037187668","https://openalex.org/W1948992892","https://openalex.org/W1886884218"],"abstract_inverted_index":{"Several":[0],"state-of-the-art":[1],"event":[2,67,78],"extraction":[3,79],"systems":[4],"employ":[5],"models":[6],"based":[7],"on":[8,144,164,179],"Support":[9],"Vector":[10],"Machines":[11],"(SVMs)":[12],"in":[13,52,113],"a":[14,74],"pipeline":[15],"architecture,":[16],"which":[17],"fails":[18],"to":[19,36,48,95,124,162,177],"exploit":[20],"the":[21,55,82,105,117,130,138,145,158,165,173,180],"joint":[22,50,119,126],"dependencies":[23],"that":[24,80],"typically":[25],"exist":[26],"among":[27],"events":[28,143],"and":[29,86,98,115,149,168,172],"arguments.":[30],"While":[31],"there":[32],"have":[33],"been":[34],"attempts":[35],"overcome":[37],"this":[38,70],"limitation":[39],"using":[40,102],"Markov":[41],"Logic":[42],"Networks":[43],"(MLNs),":[44],"it":[45],"remains":[46],"challenging":[47],"perform":[49],"inference":[51],"MLNs":[53,85,123],"when":[54],"model":[56,76],"encodes":[57],"many":[58],"high-dimensional":[59,100],"sophisticated":[60],"features":[61,101],"such":[62],"as":[63,109],"those":[64],"essential":[65],"for":[66,77,137],"extraction.":[68],"In":[69],"paper,":[71],"we":[72],"propose":[73],"new":[75],"combines":[81],"power":[83,121],"of":[84,107,122,140],"SVMs,":[87],"dwarfing":[88],"their":[89],"limitations.":[90],"The":[91],"key":[92],"idea":[93],"is":[94],"reliably":[96],"learn":[97],"process":[99],"SVMs;":[103],"encode":[104],"output":[106],"SVMs":[108],"low-dimensional,":[110],"soft":[111,131],"formulas":[112],"MLNs;":[114],"use":[116],"superior":[118],"inferencing":[120],"enforce":[125],"consistency":[127],"constraints":[128],"over":[129],"formulas.":[132],"We":[133],"evaluate":[134],"our":[135],"approach":[136,156],"task":[139,153],"extracting":[141],"biomedical":[142],"BioNLP":[146],"2013,":[147],"2011":[148],"2009":[150],"Genia":[151],"shared":[152],"datasets.":[154],"Our":[155],"yields":[157],"best":[159],"F1":[160,175],"score":[161,176],"date":[163,178],"BioNLP'13":[166],"(53.61)":[167],"BioNLP'11":[169],"(58.07)":[170],"datasets":[171],"second-best":[174],"BioNLP'09":[181],"dataset":[182],"(58.16).":[183]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":4}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}