{"id":"https://openalex.org/W2468802646","doi":"https://doi.org/10.18653/v1/s16-1193","title":"VUACLTL at SemEval 2016 Task 12: A CRF Pipeline to Clinical TempEval","display_name":"VUACLTL at SemEval 2016 Task 12: A CRF Pipeline to Clinical TempEval","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2468802646","doi":"https://doi.org/10.18653/v1/s16-1193","mag":"2468802646"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s16-1193","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1193","pdf_url":"https://doi.org/10.18653/v1/s16-1193","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/s16-1193","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064384923","display_name":"Tommaso Caselli","orcid":"https://orcid.org/0000-0003-2936-0256"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tommaso Caselli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5009134331","display_name":"Roser Morante","orcid":"https://orcid.org/0000-0002-8356-6469"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roser Morante","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1241","last_page":"1247"},"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":0.9995999932289124,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8120397329330444},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7616820335388184},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7302509546279907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6456345915794373},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.6427850723266602},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6147346496582031},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.606956958770752},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5131695866584778},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48503369092941284},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4180900454521179},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.12788301706314087},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07101786136627197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8120397329330444},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7616820335388184},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7302509546279907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6456345915794373},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.6427850723266602},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6147346496582031},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.606956958770752},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5131695866584778},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48503369092941284},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4180900454521179},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.12788301706314087},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07101786136627197},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/s16-1193","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1193","pdf_url":"https://doi.org/10.18653/v1/s16-1193","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},{"id":"pmh:vu:oai:research.vu.nl:publications/e1447bc5-8a74-4749-8545-67f0f2238277","is_oa":false,"landing_page_url":"https://research.vu.nl/en/publications/e1447bc5-8a74-4749-8545-67f0f2238277","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of SemEval-2016, 1241 - 1247","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":{"id":"doi:10.18653/v1/s16-1193","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1193","pdf_url":"https://doi.org/10.18653/v1/s16-1193","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W30314283","https://openalex.org/W2123442489","https://openalex.org/W2140244223","https://openalex.org/W2141539902","https://openalex.org/W2143733979","https://openalex.org/W2147880316","https://openalex.org/W2157275230","https://openalex.org/W2250767920","https://openalex.org/W2251220668","https://openalex.org/W2251392452","https://openalex.org/W2251873637","https://openalex.org/W2293452551","https://openalex.org/W2468432491","https://openalex.org/W2778343149"],"related_works":["https://openalex.org/W1988325893","https://openalex.org/W3029012650","https://openalex.org/W2776212826","https://openalex.org/W3214323197","https://openalex.org/W2805679416","https://openalex.org/W2805889480","https://openalex.org/W4385571001","https://openalex.org/W2805207564","https://openalex.org/W4385571880","https://openalex.org/W2806801285"],"abstract_inverted_index":{"This":[0,95],"paper":[1],"describes":[2],"VUACLTL,":[3],"the":[4,6,11,71,100,109],"system":[5,18,80],"CLTL":[7],"Lab":[8],"submitted":[9],"to":[10,49,84,91],"SemEval":[12],"2016":[13],"Task":[14],"Clinical":[15],"TempEval.":[16],"The":[17,42,79],"is":[19],"based":[20,26],"on":[21,27,99],"a":[22,28],"purely":[23],"data-driven":[24],"approach":[25],"cascade":[29],"of":[30],"seven":[31],"CRF":[32],"classifiers":[33],"which":[34,102],"use":[35],"generic":[36],"features":[37],"and":[38,58,62,70,75,88],"little":[39],"domain":[40],"knowledge.":[41],"challenge":[43],"consisted":[44],"in":[45],"six":[46],"subtasks":[47],"related":[48],"temporal":[50,59,65],"processing":[51],"clinical":[52,93],"notes":[53],"from":[54],"raw":[55],"text":[56],"(event":[57],"expression":[60],"detection":[61],"attribute":[63],"classification,":[64],"relation":[66],"classification":[67],"between":[68],"events":[69],"Document":[72],"Creation":[73],"Time,":[74],"narrative":[76],"container":[77],"detection).":[78],"was":[81],"initially":[82],"developed":[83],"process":[85,92],"newswire":[86],"texts":[87],"then":[89],"re-trained":[90],"notes.":[94],"had":[96],"an":[97],"impact":[98],"results,":[101],"are":[103],"not":[104],"equally":[105],"competitive":[106],"for":[107],"all":[108],"subtasks.":[110]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}