{"id":"https://openalex.org/W2809079601","doi":"https://doi.org/10.1145/3219819.3219899","title":"Pangloss","display_name":"Pangloss","publication_year":2018,"publication_date":"2018-07-19","ids":{"openalex":"https://openalex.org/W2809079601","doi":"https://doi.org/10.1145/3219819.3219899","mag":"2809079601"},"language":"en","primary_location":{"id":"doi:10.1145/3219819.3219899","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3219819.3219899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"article","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/A5007374520","display_name":"Michael Conover","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132246","display_name":"Workday (United States)","ror":"https://ror.org/02nn1vm89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132246"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Conover","raw_affiliation_strings":["Workday, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Workday, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210132246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008349630","display_name":"Matthew Hayes","orcid":"https://orcid.org/0000-0002-5228-4223"},"institutions":[{"id":"https://openalex.org/I4210132246","display_name":"Workday (United States)","ror":"https://ror.org/02nn1vm89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132246"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Hayes","raw_affiliation_strings":["Workday, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Workday, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210132246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073366470","display_name":"Scott Blackburn","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132246","display_name":"Workday (United States)","ror":"https://ror.org/02nn1vm89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132246"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Scott Blackburn","raw_affiliation_strings":["Workday, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Workday, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210132246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089731544","display_name":"Pete Skomoroch","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132246","display_name":"Workday (United States)","ror":"https://ror.org/02nn1vm89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132246"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pete Skomoroch","raw_affiliation_strings":["Workday, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Workday, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210132246"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017622114","display_name":"Sam Shah","orcid":"https://orcid.org/0000-0002-7743-8479"},"institutions":[{"id":"https://openalex.org/I4210132246","display_name":"Workday (United States)","ror":"https://ror.org/02nn1vm89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132246"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sam Shah","raw_affiliation_strings":["Workday, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Workday, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210132246"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.169,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59207562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"168","last_page":"176"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9994000196456909,"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":0.9991999864578247,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.885064423084259},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6001080274581909},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5924319624900818},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.5844678282737732},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4852990508079529},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.4700191020965576},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.45045405626296997},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4225255846977234},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4164218604564667},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41116490960121155},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40587687492370605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3781365752220154},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.28569549322128296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.885064423084259},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6001080274581909},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5924319624900818},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.5844678282737732},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4852990508079529},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.4700191020965576},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.45045405626296997},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4225255846977234},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4164218604564667},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41116490960121155},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40587687492370605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3781365752220154},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.28569549322128296},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3219819.3219899","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3219819.3219899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W86887328","https://openalex.org/W102708294","https://openalex.org/W1541691357","https://openalex.org/W1574911124","https://openalex.org/W1596986901","https://openalex.org/W1880262756","https://openalex.org/W1964189668","https://openalex.org/W1968625547","https://openalex.org/W1988157164","https://openalex.org/W2020278455","https://openalex.org/W2022166150","https://openalex.org/W2057047055","https://openalex.org/W2100341149","https://openalex.org/W2115352105","https://openalex.org/W2123442489","https://openalex.org/W2127289991","https://openalex.org/W2127426251","https://openalex.org/W2131357087","https://openalex.org/W2135451108","https://openalex.org/W2139694477","https://openalex.org/W2147152072","https://openalex.org/W2150815390","https://openalex.org/W2150871663","https://openalex.org/W2153848201","https://openalex.org/W2158028897","https://openalex.org/W2164455818","https://openalex.org/W2187561416","https://openalex.org/W2247119764","https://openalex.org/W2250387192","https://openalex.org/W2250999864","https://openalex.org/W2294546627","https://openalex.org/W2337969891","https://openalex.org/W2409706897","https://openalex.org/W2436001372","https://openalex.org/W2505055145","https://openalex.org/W2584004798","https://openalex.org/W2601243251","https://openalex.org/W2604272474","https://openalex.org/W2618735189","https://openalex.org/W2771472444","https://openalex.org/W2799915114","https://openalex.org/W2950133940","https://openalex.org/W2962769558","https://openalex.org/W4239696231","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W1541691357","https://openalex.org/W2090135255","https://openalex.org/W2168409722","https://openalex.org/W2548972888","https://openalex.org/W2026505290","https://openalex.org/W2782437235","https://openalex.org/W1993715838","https://openalex.org/W2359088421","https://openalex.org/W2181629536","https://openalex.org/W2119465010"],"abstract_inverted_index":{"Entity":[0],"linking":[1],"is":[2,23],"the":[3],"task":[4],"of":[5],"mapping":[6],"potentially":[7],"ambiguous":[8],"terms":[9],"in":[10,16,35,64,126,158,164],"text":[11,55,79],"to":[12,84,119,129,148],"their":[13],"constituent":[14],"entities":[15],"a":[17,81,91,102,110,140,145],"knowledge":[18,43],"base":[19],"like":[20,40,60],"Wikipedia.":[21],"This":[22,87],"useful":[24],"for":[25,94],"organizing":[26],"content,":[27],"extracting":[28],"structured":[29],"data":[30],"from":[31],"textual":[32],"documents,":[33],"and":[34,46,152,161],"machine":[36],"learning":[37],"relevance":[38],"applications":[39],"semantic":[41,111],"search,":[42],"graph":[44],"construction,":[45],"question":[47],"answering.":[48],"Traditionally,":[49],"this":[50,85],"work":[51],"has":[52,57],"focused":[53],"on":[54,97,115],"that":[56],"been":[58],"well-formed,":[59],"news":[61],"articles,":[62],"but":[63],"common":[65],"real":[66],"world":[67],"datasets":[68],"such":[69,167],"as":[70,168],"messaging,":[71],"resumes,":[72],"or":[73,132],"short-form":[74],"social":[75],"media,":[76],"non-grammatical,":[77],"loosely-structured":[78],"adds":[80],"new":[82],"dimension":[83],"problem.":[86],"paper":[88],"presents":[89],"Pangloss,":[90],"production":[92],"system":[93],"entity":[95],"disambiguation":[96,157,163],"noisy":[98],"text.":[99],"Pangloss":[100,138],"combines":[101],"probabilistic":[103],"linear-time":[104],"key":[105],"phrase":[106],"identification":[107],"algorithm":[108],"with":[109,144],"similarity":[112],"engine":[113],"based":[114],"context-dependent":[116],"document":[117],"embeddings":[118],"achieve":[120],"better":[121],"than":[122],"state-of-the-art":[123],"results":[124],"(>5%":[125],"F1)":[127],"compared":[128],"other":[130],"research":[131],"commercially":[133],"available":[134],"systems.":[135],"In":[136],"addition,":[137],"leverages":[139],"local":[141],"embedded":[142],"database":[143],"tiered":[146],"architecture":[147],"house":[149],"its":[150],"statistics":[151],"metadata,":[153],"which":[154],"allows":[155],"rapid":[156],"streaming":[159],"contexts":[160],"on-device":[162],"low-memory":[165],"environments":[166],"mobile":[169],"phones.":[170]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2018-06-29T00:00:00"}