{"id":"https://openalex.org/W2987432520","doi":"https://doi.org/10.26615/978-954-452-056-4_015","title":"Quasi Bidirectional Encoder Representations from Transformers for Word Sense Disambiguation","display_name":"Quasi Bidirectional Encoder Representations from Transformers for Word Sense Disambiguation","publication_year":2019,"publication_date":"2019-10-22","ids":{"openalex":"https://openalex.org/W2987432520","doi":"https://doi.org/10.26615/978-954-452-056-4_015","mag":"2987432520"},"language":"en","primary_location":{"id":"doi:10.26615/978-954-452-056-4_015","is_oa":true,"landing_page_url":"https://doi.org/10.26615/978-954-452-056-4_015","pdf_url":"https://doi.org/10.26615/978-954-452-056-4_015","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings - Natural Language Processing in a Deep Learning World","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.26615/978-954-452-056-4_015","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079283776","display_name":"Michele Bevilacqua","orcid":"https://orcid.org/0000-0002-2717-1454"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Michele Bevilacqua","raw_affiliation_strings":["Department of Computer Science Sapienza University of Rome"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science Sapienza University of Rome","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026648049","display_name":"Roberto Navigli","orcid":"https://orcid.org/0000-0003-3831-9706"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roberto Navigli","raw_affiliation_strings":["Department of Computer Science Sapienza University of Rome"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science Sapienza University of Rome","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079283776"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5897,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88096917,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"122","last_page":"131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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":0.9998999834060669,"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/T13629","display_name":"Text Readability and Simplification","score":0.9936000108718872,"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/concatenation","display_name":"Concatenation (mathematics)","score":0.9015772342681885},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8448396325111389},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7656068801879883},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7071884870529175},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6471900343894958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6405484676361084},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5801041722297668},{"id":"https://openalex.org/keywords/word-sense-disambiguation","display_name":"Word-sense disambiguation","score":0.5533499717712402},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5137132406234741},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.44942331314086914},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.4246599078178406},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.42056405544281006},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37064796686172485},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.20955893397331238},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.1313387155532837},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06588771939277649}],"concepts":[{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.9015772342681885},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8448396325111389},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7656068801879883},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7071884870529175},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6471900343894958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6405484676361084},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5801041722297668},{"id":"https://openalex.org/C51646954","wikidata":"https://www.wikidata.org/wiki/Q48522","display_name":"Word-sense disambiguation","level":3,"score":0.5533499717712402},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5137132406234741},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.44942331314086914},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.4246599078178406},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.42056405544281006},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37064796686172485},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.20955893397331238},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.1313387155532837},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06588771939277649},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.26615/978-954-452-056-4_015","is_oa":true,"landing_page_url":"https://doi.org/10.26615/978-954-452-056-4_015","pdf_url":"https://doi.org/10.26615/978-954-452-056-4_015","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings - Natural Language Processing in a Deep Learning World","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.uniroma1.it:11573/1350045","is_oa":true,"landing_page_url":"http://hdl.handle.net/11573/1350045","pdf_url":"http://hdl.handle.net/11573/1350045","source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.26615/978-954-452-056-4_015","is_oa":true,"landing_page_url":"https://doi.org/10.26615/978-954-452-056-4_015","pdf_url":"https://doi.org/10.26615/978-954-452-056-4_015","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings - Natural Language Processing in a Deep Learning World","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G4628848537","display_name":"Multilingual, Open-text Unified Syntax-independent SEmantics","funder_award_id":"726487","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4956428346","display_name":null,"funder_award_id":"Horizon 2020 research and innovatio","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5036817778","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innov","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8051717526","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8318064016","display_name":null,"funder_award_id":"Horizon","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8633428685","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innovat","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2987432520.pdf","grobid_xml":"https://content.openalex.org/works/W2987432520.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W135437175","https://openalex.org/W1902237438","https://openalex.org/W2038721957","https://openalex.org/W2101293500","https://openalex.org/W2131540451","https://openalex.org/W2133564696","https://openalex.org/W2194775991","https://openalex.org/W2250539671","https://openalex.org/W2250718062","https://openalex.org/W2251291469","https://openalex.org/W2251529656","https://openalex.org/W2251581485","https://openalex.org/W2436001372","https://openalex.org/W2507974895","https://openalex.org/W2518202280","https://openalex.org/W2519314406","https://openalex.org/W2550186622","https://openalex.org/W2740782137","https://openalex.org/W2757205734","https://openalex.org/W2757601816","https://openalex.org/W2758017605","https://openalex.org/W2805581412","https://openalex.org/W2806512283","https://openalex.org/W2813700965","https://openalex.org/W2880875857","https://openalex.org/W2896457183","https://openalex.org/W2899220776","https://openalex.org/W2914120296","https://openalex.org/W2927103915","https://openalex.org/W2951368271","https://openalex.org/W2962739339","https://openalex.org/W2962784628","https://openalex.org/W2963026768","https://openalex.org/W2963034893","https://openalex.org/W2963246595","https://openalex.org/W2963341956","https://openalex.org/W2963347649","https://openalex.org/W2963403868","https://openalex.org/W2963631907","https://openalex.org/W2963956638","https://openalex.org/W2964054038","https://openalex.org/W2964189868","https://openalex.org/W2964308564","https://openalex.org/W4297771995","https://openalex.org/W4385245566","https://openalex.org/W4394666973"],"related_works":["https://openalex.org/W2101293500","https://openalex.org/W2384058382","https://openalex.org/W2000205775","https://openalex.org/W2251529656","https://openalex.org/W2324822715","https://openalex.org/W2330879361","https://openalex.org/W2140343536","https://openalex.org/W2188275805","https://openalex.org/W3012220652","https://openalex.org/W2062413478"],"abstract_inverted_index":{"While":[0],"contextualized":[1,34],"embeddings":[2,35],"have":[3],"produced":[4],"performance":[5],"breakthroughs":[6],"in":[7],"many":[8],"Natural":[9],"Language":[10],"Processing":[11],"(NLP)":[12],"tasks,":[13],"Word":[14],"Sense":[15],"Disambiguation":[16],"(WSD)":[17],"has":[18],"not":[19],"benefited":[20],"from":[21],"them":[22],"yet.":[23],"In":[24],"this":[25],"paper,":[26],"we":[27,57],"introduce":[28],"QBERT,":[29],"a":[30,40,55,62,85],"Transformerbased":[31],"architecture":[32],"for":[33,50],"which":[36],"makes":[37],"use":[38],"of":[39,69,75],"coattentive":[41],"layer":[42],"to":[43,60],"produce":[44],"more":[45],"deeply":[46],"bidirectional":[47],"representations,":[48],"better-fitting":[49],"the":[51,67,70,73],"WSD":[52,63],"task.":[53],"As":[54],"result,":[56],"are":[58],"able":[59],"train":[61],"system":[64],"that":[65],"beats":[66],"state":[68],"art":[71],"on":[72],"concatenation":[74],"all":[76],"evaluation":[77],"datasets":[78],"by":[79],"over":[80],"3":[81],"points,":[82],"also":[83],"outperforming":[84],"comparable":[86],"model":[87],"using":[88],"ELMo.":[89]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
