{"id":"https://openalex.org/W2955452806","doi":"https://doi.org/10.18653/v1/w18-5525","title":"Team SWEEPer: Joint Sentence Extraction and Fact Checking with Pointer Networks","display_name":"Team SWEEPer: Joint Sentence Extraction and Fact Checking with Pointer Networks","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2955452806","doi":"https://doi.org/10.18653/v1/w18-5525","mag":"2955452806"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w18-5525","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-5525","pdf_url":"https://www.aclweb.org/anthology/W18-5525.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 First Workshop on Fact Extraction and VERification (FEVER)","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/W18-5525.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037985811","display_name":"Christopher Hidey","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Hidey","raw_affiliation_strings":["Amazon AI Lab","Department of Computer Science Columbia University New York, NY 10027"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon AI Lab","institution_ids":["https://openalex.org/I1311688040"]},{"raw_affiliation_string":"Department of Computer Science Columbia University New York, NY 10027","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038581447","display_name":"Mona Diab","orcid":"https://orcid.org/0000-0002-7696-1436"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mona Diab","raw_affiliation_strings":["Department of Computer Science Columbia University New York, NY 10027","Amazon AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science Columbia University New York, NY 10027","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Amazon AI Lab","institution_ids":["https://openalex.org/I1311688040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"150","last_page":"155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/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/T13629","display_name":"Text Readability and Simplification","score":0.9955999851226807,"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":0.8338942527770996},{"id":"https://openalex.org/keywords/pointer","display_name":"Pointer (user interface)","score":0.7397550344467163},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6879633665084839},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6577576398849487},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6017661094665527},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5578871369361877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5565563440322876},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.4847097396850586},{"id":"https://openalex.org/keywords/statement","display_name":"Statement (logic)","score":0.45494839549064636},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4340320825576782},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3798093795776367},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3432105779647827},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1542675793170929},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.10439810156822205}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8338942527770996},{"id":"https://openalex.org/C150202949","wikidata":"https://www.wikidata.org/wiki/Q107602","display_name":"Pointer (user interface)","level":2,"score":0.7397550344467163},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6879633665084839},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6577576398849487},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6017661094665527},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5578871369361877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5565563440322876},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.4847097396850586},{"id":"https://openalex.org/C2777026412","wikidata":"https://www.wikidata.org/wiki/Q2684591","display_name":"Statement (logic)","level":2,"score":0.45494839549064636},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4340320825576782},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3798093795776367},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3432105779647827},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1542675793170929},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.10439810156822205},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w18-5525","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-5525","pdf_url":"https://www.aclweb.org/anthology/W18-5525.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 First Workshop on Fact Extraction and VERification (FEVER)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w18-5525","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-5525","pdf_url":"https://www.aclweb.org/anthology/W18-5525.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 First Workshop on Fact Extraction and VERification (FEVER)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2955452806.pdf","grobid_xml":"https://content.openalex.org/works/W2955452806.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1793121960","https://openalex.org/W2123442489","https://openalex.org/W2250539671","https://openalex.org/W2507756961","https://openalex.org/W2565836511","https://openalex.org/W2574535369","https://openalex.org/W2608787653","https://openalex.org/W2899771611","https://openalex.org/W2951008357","https://openalex.org/W2952138241","https://openalex.org/W2953300870","https://openalex.org/W2962985038","https://openalex.org/W2962985882","https://openalex.org/W2963716836","https://openalex.org/W2963842982","https://openalex.org/W2963961878","https://openalex.org/W2964121744"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W2115758952","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W2349927912","https://openalex.org/W2551029266","https://openalex.org/W1976369278"],"abstract_inverted_index":{"Many":[0],"tasks":[1,96],"such":[2],"as":[3],"question":[4],"answering":[5],"and":[6,40,52,115,130],"reading":[7],"comprehension":[8],"rely":[9],"on":[10,35,99,132,143],"information":[11],"extracted":[12],"from":[13,21,26,50,76],"unreliable":[14,28],"sources.":[15],"These":[16],"systems":[17],"would":[18,105],"thus":[19,125],"benefit":[20],"knowing":[22],"whether":[23,54],"a":[24,43,55,72,85],"statement":[25],"an":[27,102],"source":[29],"is":[30,57,65,71,122],"correct.":[31],"We":[32,124],"present":[33],"experiments":[34],"the":[36,82,107,110,119,133,144,155],"FEVER":[37,134],"(Fact":[38],"Extraction":[39],"VERification)":[41],"task,":[42],"shared":[44,135],"task":[45,73],"that":[46,74,92,121],"involves":[47],"selecting":[48],"sentences":[49],"Wikipedia":[51],"predicting":[53],"claim":[56,86,111],"supported":[58],"by":[59],"those":[60],"sentences,":[61],"refuted,":[62],"or":[63,80],"there":[64],"not":[66,77],"enough":[67],"information.":[68],"Fact":[69],"checking":[70],"benefits":[75],"only":[78,118],"asserting":[79],"disputing":[81],"veracity":[83,108],"of":[84,109,154],"but":[87],"also":[88,116],"finding":[89,113],"evidence":[90,114,120],"for":[91],"position.":[93],"As":[94],"these":[95],"are":[97],"dependent":[98],"each":[100],"other,":[101],"ideal":[103],"model":[104,127],"consider":[106],"when":[112],"find":[117],"relevant.":[123],"jointly":[126],"sentence":[128],"extraction":[129],"verification":[131],"task.":[136],"Among":[137],"all":[138],"participants,":[139],"we":[140],"ranked":[141],"5th":[142],"blind":[145],"test":[146],"set":[147],"(prior":[148],"to":[149],"any":[150],"additional":[151],"human":[152],"evaluation":[153],"evidence).":[156]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
