{"id":"https://openalex.org/W2463713334","doi":"https://doi.org/10.18653/v1/e17-1058","title":"Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema","display_name":"Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2463713334","doi":"https://doi.org/10.18653/v1/e17-1058","mag":"2463713334"},"language":"en","primary_location":{"id":"doi:10.18653/v1/e17-1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/e17-1058","pdf_url":"https://www.aclweb.org/anthology/E17-1058.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 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/E17-1058.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008189176","display_name":"Patrick Verga","orcid":null},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patrick Verga","raw_affiliation_strings":["College of Information and Computer Sciences University of Massachusetts Amherst","University of Massachusetts Amherst, Amherst Center, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Computer Sciences University of Massachusetts Amherst","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst Center, United States","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043840749","display_name":"Arvind Neelakantan","orcid":null},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arvind Neelakantan","raw_affiliation_strings":["College of Information and Computer Sciences University of Massachusetts Amherst","University of Massachusetts Amherst, Amherst Center, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Computer Sciences University of Massachusetts Amherst","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst Center, United States","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107835063","display_name":"Andrew McCallum","orcid":null},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]},{"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","US"],"is_corresponding":false,"raw_author_name":"Andrew McCallum","raw_affiliation_strings":["College of Information and Computer Sciences University of Massachusetts Amherst","University College London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Computer Sciences University of Massachusetts Amherst","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4153,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60416608,"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":"613","last_page":"622"},"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":0.9998000264167786,"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":0.9979000091552734,"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/row","display_name":"Row","score":0.783986508846283},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7439435720443726},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.6665652394294739},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6457569599151611},{"id":"https://openalex.org/keywords/row-and-column-spaces","display_name":"Row and column spaces","score":0.5160824656486511},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41836386919021606},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4012239873409271},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3380615711212158},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.28066182136535645},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13560619950294495}],"concepts":[{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.783986508846283},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7439435720443726},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.6665652394294739},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6457569599151611},{"id":"https://openalex.org/C104140500","wikidata":"https://www.wikidata.org/wiki/Q2088159","display_name":"Row and column spaces","level":3,"score":0.5160824656486511},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41836386919021606},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4012239873409271},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3380615711212158},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.28066182136535645},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13560619950294495}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/e17-1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/e17-1058","pdf_url":"https://www.aclweb.org/anthology/E17-1058.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 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1606.05804","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1606.05804","pdf_url":"https://arxiv.org/pdf/1606.05804","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2463713334","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1606.05804.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1606.05804","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1606.05804","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/e17-1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/e17-1058","pdf_url":"https://www.aclweb.org/anthology/E17-1058.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 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.75,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2011866053","display_name":"III: Medium: Constructing Knowledge Bases by Extracting Entity-Relations and Meanings from Natural Language via \"Universal Schema\"","funder_award_id":"1514053","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G414571346","display_name":null,"funder_award_id":"FA8750-13-2-0020","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5217516660","display_name":null,"funder_award_id":"IIS-1514053","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2463713334.pdf","grobid_xml":"https://content.openalex.org/works/W2463713334.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W174427690","https://openalex.org/W205829674","https://openalex.org/W1512387364","https://openalex.org/W1533230146","https://openalex.org/W1604644367","https://openalex.org/W1756422141","https://openalex.org/W1852412531","https://openalex.org/W2022166150","https://openalex.org/W2039127023","https://openalex.org/W2042792636","https://openalex.org/W2090641502","https://openalex.org/W2094728533","https://openalex.org/W2107598941","https://openalex.org/W2127426251","https://openalex.org/W2127795553","https://openalex.org/W2140310134","https://openalex.org/W2146772539","https://openalex.org/W2158515176","https://openalex.org/W2162456950","https://openalex.org/W2184957013","https://openalex.org/W2250635077","https://openalex.org/W2252136820","https://openalex.org/W2283196293","https://openalex.org/W2406945108","https://openalex.org/W2515462165","https://openalex.org/W2949403529","https://openalex.org/W2950527759","https://openalex.org/W2950895672","https://openalex.org/W2951008357","https://openalex.org/W2951622387","https://openalex.org/W2952155763","https://openalex.org/W2963929497","https://openalex.org/W2964121744","https://openalex.org/W2964224278","https://openalex.org/W2964308564"],"related_works":["https://openalex.org/W2963374550","https://openalex.org/W2952235283","https://openalex.org/W2889392797","https://openalex.org/W2971708730","https://openalex.org/W2905462022","https://openalex.org/W2956420974","https://openalex.org/W2928728590","https://openalex.org/W3177994754","https://openalex.org/W1563734366","https://openalex.org/W3080817367","https://openalex.org/W2891743895","https://openalex.org/W3180299858","https://openalex.org/W3170215906","https://openalex.org/W2936649169","https://openalex.org/W3138607860","https://openalex.org/W2788824939","https://openalex.org/W3196690920","https://openalex.org/W2927054315","https://openalex.org/W3081607678","https://openalex.org/W2883854254"],"abstract_inverted_index":{"Universal":[0],"schema":[1,22],"predicts":[2],"the":[3,17,70,101,138,146,149,217,220,236],"types":[4,25,38,74],"of":[5,19,72,103,145,148,206,219],"entities":[6,66,107,181],"and":[7,61,93,196,223],"relations":[8,195],"in":[9,176],"a":[10,52,86,117,134,141,172],"knowledge":[11],"base":[12],"(KB)":[13],"by":[14,184],"jointly":[15],"embedding":[16,89],"union":[18],"all":[20],"available":[21,241],"types-not":[23],"only":[24],"from":[26,43],"multiple":[27],"structured":[28],"databases":[29],"(such":[30],"as":[31,40,51,171,239],"Freebase":[32],"or":[33,64,75,108,188],"Wikipedia":[34],"infoboxes),":[35],"but":[36],"also":[37],"expressed":[39],"textual":[41,187],"patterns":[42],"raw":[44],"text.":[45],"This":[46],"prediction":[47],"is":[48],"typically":[49],"modeled":[50],"matrix":[53,84],"completion":[54],"problem,":[55],"with":[56,157,234],"one":[57,63],"type":[58],"per":[59,67],"column,":[60],"either":[62],"two":[65],"row":[68,92,119,135],"(in":[69],"case":[71],"entity":[73,197],"binary":[76],"relation":[77],"types,":[78,198],"respectively).":[79],"Factorizing":[80],"this":[81,97],"sparsely":[82],"observed":[83,150],"yields":[85],"learned":[87,142],"vector":[88,136],"for":[90,106,152],"each":[91,94],"column.":[95],"In":[96,191],"paper":[98],"we":[99,132,199,214,226],"explore":[100],"problem":[102],"making":[104],"predictions":[105,230],"entity-pairs":[109],"unseen":[110,232],"at":[111,129,242],"training":[112,243],"time":[113],"(and":[114],"hence":[115],"without":[116],"pre-learned":[118],"embedding).":[120],"We":[121,155],"propose":[122],"an":[123,204],"approach":[124,167],"having":[125,203],"no":[126],"per-row":[127],"parameters":[128,209],"all;":[130],"rather":[131],"produce":[133],"on":[137],"fly":[139],"using":[140],"aggregation":[143,159],"function":[144],"vectors":[147],"columns":[151],"that":[153,177,201],"row.":[154],"experiment":[156],"various":[158],"functions,":[160],"including":[161],"neural":[162],"network":[163],"attention":[164],"models.":[165],"Our":[166],"can":[168,215,227],"be":[169],"understood":[170],"natural":[173],"language":[174],"database,":[175],"questions":[178],"about":[179,231],"KB":[180],"are":[182],"answered":[183],"attending":[185],"to":[186],"database":[189],"evidence.":[190],"experiments":[192],"predicting":[193],"both":[194],"demonstrate":[200],"despite":[202],"order":[205],"magnitude":[207],"fewer":[208],"than":[210],"traditional":[211,221],"universal":[212],"schema,":[213],"match":[216],"accuracy":[218,238],"model,":[222],"more":[224],"importantly,":[225],"now":[228],"make":[229],"rows":[233,240],"nearly":[235],"same":[237],"time.":[244]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}