{"id":"https://openalex.org/W2511134827","doi":"https://doi.org/10.18653/v1/s16-2019","title":"Orthogonality regularizer for question answering","display_name":"Orthogonality regularizer for question answering","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2511134827","doi":"https://doi.org/10.18653/v1/s16-2019","mag":"2511134827"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s16-2019","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-2019","pdf_url":"https://www.aclweb.org/anthology/S16-2019.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 Fifth Joint Conference on Lexical and Computational Semantics","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/S16-2019.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073007032","display_name":"Chunyang Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Chunyang Xiao","raw_affiliation_strings":["Xerox Research Centre Europe, Grenoble, France","Xerox Research Centre Europe [Meylan] (Xerox Research Centre Europe 6 Chemin de Maupertuis 38240 Meylan, FRANCE - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xerox Research Centre Europe, Grenoble, France","institution_ids":["https://openalex.org/I33976269"]},{"raw_affiliation_string":"Xerox Research Centre Europe [Meylan] (Xerox Research Centre Europe 6 Chemin de Maupertuis 38240 Meylan, FRANCE - France)","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090750283","display_name":"Guillaume Bouchard","orcid":"https://orcid.org/0009-0006-5332-0923"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Guillaume Bouchard","raw_affiliation_strings":["University College London, United Kingdom","UCL - University College of London [London] (Gower Street, London WC1E 6BT - United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"UCL - University College of London [London] (Gower Street, London WC1E 6BT - United Kingdom)","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059468860","display_name":"Marc Dymetman","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Marc Dymetman","raw_affiliation_strings":["Xerox Research Centre Europe, Grenoble, France","Xerox Research Centre Europe [Meylan] (Xerox Research Centre Europe 6 Chemin de Maupertuis 38240 Meylan, FRANCE - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xerox Research Centre Europe, Grenoble, France","institution_ids":["https://openalex.org/I33976269"]},{"raw_affiliation_string":"Xerox Research Centre Europe [Meylan] (Xerox Research Centre Europe 6 Chemin de Maupertuis 38240 Meylan, FRANCE - France)","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087459652","display_name":"Claire Gardent","orcid":"https://orcid.org/0000-0002-3805-6662"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210121838","display_name":"Laboratoire Lorrain de Recherche en Informatique et ses Applications","ror":"https://ror.org/02vnf0c38","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I277688954","https://openalex.org/I4210107720","https://openalex.org/I4210121838","https://openalex.org/I4210159245","https://openalex.org/I90183372"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Claire Gardent","raw_affiliation_strings":["CNRS, LORIA, Nancy, France","SYNALP - Natural Language Processing : representations, inference and semantics (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS, LORIA, Nancy, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I4210121838"]},{"raw_affiliation_string":"SYNALP - Natural Language Processing : representations, inference and semantics (France)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"142","last_page":"147"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9987999796867371,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9965999722480774,"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/orthogonality","display_name":"Orthogonality","score":0.8307485580444336},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7480716705322266},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7233865261077881},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7012941241264343},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6935311555862427},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5752114653587341},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5124419331550598},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.49074944853782654},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.4809812307357788},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.4789170026779175},{"id":"https://openalex.org/keywords/lying","display_name":"Lying","score":0.46641644835472107},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.43505799770355225},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33179664611816406},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19401532411575317}],"concepts":[{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.8307485580444336},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7480716705322266},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7233865261077881},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7012941241264343},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6935311555862427},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5752114653587341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5124419331550598},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.49074944853782654},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.4809812307357788},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.4789170026779175},{"id":"https://openalex.org/C119421448","wikidata":"https://www.wikidata.org/wiki/Q2268776","display_name":"Lying","level":2,"score":0.46641644835472107},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.43505799770355225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33179664611816406},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19401532411575317},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/s16-2019","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-2019","pdf_url":"https://www.aclweb.org/anthology/S16-2019.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 Fifth Joint Conference on Lexical and Computational Semantics","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-01623819v1","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-01623819","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"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":"*SEM 2016,. The Fifth Joint Conference on Lexical and Computational Semantics, Aug 2016, Berlin, Germany. pp.142 - 147, &#x27E8;10.18653/v1/S16-2019&#x27E9;","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.18653/v1/s16-2019","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-2019","pdf_url":"https://www.aclweb.org/anthology/S16-2019.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 Fifth Joint Conference on Lexical and Computational Semantics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2511134827.pdf","grobid_xml":"https://content.openalex.org/works/W2511134827.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W188912188","https://openalex.org/W1503259811","https://openalex.org/W1801721664","https://openalex.org/W1894439495","https://openalex.org/W1937075317","https://openalex.org/W1985768342","https://openalex.org/W2090243146","https://openalex.org/W2094728533","https://openalex.org/W2126170172","https://openalex.org/W2131726681","https://openalex.org/W2146502635","https://openalex.org/W2147152072","https://openalex.org/W2148721079","https://openalex.org/W2167187514","https://openalex.org/W2250225488","https://openalex.org/W2251143283","https://openalex.org/W2251287417","https://openalex.org/W2252136820","https://openalex.org/W2596356468","https://openalex.org/W2950133940","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W2955910435","https://openalex.org/W2888123326","https://openalex.org/W2501458630","https://openalex.org/W2982312151","https://openalex.org/W4246089694","https://openalex.org/W3134247745","https://openalex.org/W4226243593","https://openalex.org/W3172691639","https://openalex.org/W2963582704","https://openalex.org/W3182020042"],"abstract_inverted_index":{"Learning":[0],"embeddings":[1,45,65],"of":[2,39,46,53],"words":[3],"and":[4,23],"knowledge":[5,68],"base":[6],"elements":[7],"is":[8],"a":[9,41,83],"promising":[10],"approach":[11],"for":[12],"open":[13],"domain":[14],"question":[15,85],"answering.":[16],"Based":[17],"on":[18,82],"the":[19,31,37,44,60,64,77],"remark":[20],"that":[21,62,75],"relations":[22],"entities":[24,47],"are":[25],"distinct":[26],"object":[27],"types":[28],"lying":[29],"in":[30],"same":[32],"embedding":[33],"space,":[34],"we":[35],"analyze":[36],"benefit":[38],"adding":[40],"regularizer":[42,78],"favoring":[43],"to":[48,51],"be":[49],"orthogonal":[50],"those":[52],"relations.":[54],"The":[55,72],"main":[56],"motivation":[57],"comes":[58],"from":[59],"observation":[61],"modifying":[63],"using":[66],"prior":[67],"often":[69],"helps":[70],"performance.":[71],"experiments":[73],"show":[74],"incorporating":[76],"yields":[79],"better":[80],"results":[81],"challenging":[84],"answering":[86],"benchmark.":[87]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
