{"id":"https://openalex.org/W2945730924","doi":"https://doi.org/10.1145/3308560.3316478","title":"Information Extraction with Humans in the Loop","display_name":"Information Extraction with Humans in the Loop","publication_year":2019,"publication_date":"2019-05-13","ids":{"openalex":"https://openalex.org/W2945730924","doi":"https://doi.org/10.1145/3308560.3316478","mag":"2945730924"},"language":"en","primary_location":{"id":"doi:10.1145/3308560.3316478","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3308560.3316478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of The 2019 World Wide Web Conference","raw_type":"proceedings-article"},"type":"conference-paper","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/A5045091443","display_name":"Anna Lisa Gentile","orcid":"https://orcid.org/0000-0002-6401-4175"},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anna Lisa Gentile","raw_affiliation_strings":["IBM Research Almaden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Almaden","institution_ids":["https://openalex.org/I4210085935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5045091443"],"corresponding_institution_ids":["https://openalex.org/I4210085935"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03746275,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1264","last_page":"1264"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9991999864578247,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9991999864578247,"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":0.9986000061035156,"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":0.9983000159263611,"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":0.8344107866287231},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.7360309362411499},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6864888668060303},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5540058612823486},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.553591787815094},{"id":"https://openalex.org/keywords/human-in-the-loop","display_name":"Human-in-the-loop","score":0.4474421441555023},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.44723019003868103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37839987874031067},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.359078586101532},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32173073291778564}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8344107866287231},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.7360309362411499},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6864888668060303},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5540058612823486},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.553591787815094},{"id":"https://openalex.org/C2780626000","wikidata":"https://www.wikidata.org/wiki/Q5936775","display_name":"Human-in-the-loop","level":2,"score":0.4474421441555023},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.44723019003868103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37839987874031067},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.359078586101532},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32173073291778564},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3308560.3316478","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3308560.3316478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of The 2019 World Wide Web Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.800000011920929,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2779326814","https://openalex.org/W2806495905","https://openalex.org/W2809631449"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2888033806","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W2444550338","https://openalex.org/W2369351710","https://openalex.org/W2594363579"],"abstract_inverted_index":{"Information":[0],"Extraction":[1],"(IE)":[2],"techniques":[3,57,98],"enables":[4],"us":[5],"to":[6,44,52,72,86,96,102],"distill":[7],"Knowledge":[8],"from":[9,28,60],"the":[10,17,22,46,69,116],"abundantly":[11],"available":[12],"unstructured":[13],"content.":[14],"Some":[15],"of":[16,25,68,90,106],"basic":[18],"IE":[19,56,97],"methods":[20,82],"include":[21],"automatic":[23,81],"extraction":[24,47,50,123],"relevant":[26],"entities":[27],"text":[29],"(e.g.":[30],"places,":[31],"dates,":[32],"people,":[33],"...),":[34],"understanding":[35],"relations":[36],"among":[37],"them,":[38],"building":[39],"semantic":[40],"resources":[41],"(dictionaries,":[42],"ontologies)":[43],"inform":[45],"tasks,":[48],"connecting":[49],"results":[51],"standard":[53],"classification":[54],"resources.":[55],"cannot":[58],"decouple":[59],"human":[61,78,107,117],"input":[62],"-":[63],"at":[64],"bare":[65],"minimum":[66],"some":[67],"data":[70],"needs":[71],"be":[73],"manually":[74],"annotated":[75],"by":[76],"a":[77],"so":[79],"that":[80],"can":[83],"learn":[84],"patterns":[85],"recognize":[87],"certain":[88],"type":[89],"information.":[91],"The":[92],"human-in-the-loop":[93],"paradigm":[94],"applied":[95],"focuses":[99],"on":[100],"how":[101,112],"better":[103],"take":[104],"advantage":[105],"annotations":[108],"(the":[109],"recorded":[110],"observations),":[111],"much":[113],"interaction":[114],"with":[115],"is":[118],"needed":[119],"for":[120],"each":[121],"specific":[122],"task.":[124]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}