{"id":"https://openalex.org/W2896391192","doi":"https://doi.org/10.18653/v1/p17-2057","title":"Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks","display_name":"Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2896391192","doi":"https://doi.org/10.18653/v1/p17-2057","mag":"2896391192"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p17-2057","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-2057","pdf_url":"https://www.aclweb.org/anthology/P17-2057.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 55th Annual Meeting of the Association for\n          Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P17-2057.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106307747","display_name":"Rajarshi Das","orcid":"https://orcid.org/0009-0009-9348-5265"},"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":true,"raw_author_name":"Rajarshi Das","raw_affiliation_strings":["College of Information and Computer Sciences, University of Massachusetts Amherst","University of Massachusetts Amherst, Amherst Center, United States"],"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/A5018931712","display_name":"Manzil Zaheer","orcid":"https://orcid.org/0000-0001-7092-8515"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manzil Zaheer","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University  School of Informatics, University of Edinburgh","Carnegie Mellon University, Pittsburgh, United States"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University  School of Informatics, University of Edinburgh","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, United States","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102886212","display_name":"Siva Reddy","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siva Reddy","raw_affiliation_strings":["Stanford University, Stanford, United States"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, United States","institution_ids":["https://openalex.org/I97018004"]}]},{"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"],"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":4,"corresponding_author_ids":["https://openalex.org/A5106307747"],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":4.7808,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.96016033,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"358","last_page":"365"},"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":0.9993000030517578,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/schema","display_name":"Schema (genetic algorithms)","score":0.8406369686126709},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7985084056854248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7737418413162231},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.6136035919189453},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.44655317068099976},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4293833374977112},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4200742244720459}],"concepts":[{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.8406369686126709},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7985084056854248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7737418413162231},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.6136035919189453},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.44655317068099976},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4293833374977112},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4200742244720459}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/p17-2057","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-2057","pdf_url":"https://www.aclweb.org/anthology/P17-2057.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 55th Annual Meeting of the Association for\n          Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1704.08384","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1704.08384","pdf_url":"https://arxiv.org/pdf/1704.08384","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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:2896391192","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1704.08384.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.1704.08384","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1704.08384","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"doi:10.18653/v1/p17-2057","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-2057","pdf_url":"https://www.aclweb.org/anthology/P17-2057.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 55th Annual Meeting of the Association for\n          Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6000000238418579,"display_name":"Quality Education"}],"awards":[{"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"}],"funders":[{"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/W2896391192.pdf","grobid_xml":"https://content.openalex.org/works/W2896391192.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W147290778","https://openalex.org/W580074167","https://openalex.org/W1493490255","https://openalex.org/W1496189301","https://openalex.org/W1512387364","https://openalex.org/W1604644367","https://openalex.org/W1646084575","https://openalex.org/W1852412531","https://openalex.org/W1934264538","https://openalex.org/W1979263599","https://openalex.org/W1980910426","https://openalex.org/W2016753842","https://openalex.org/W2064675550","https://openalex.org/W2086511124","https://openalex.org/W2090243146","https://openalex.org/W2094728533","https://openalex.org/W2107598941","https://openalex.org/W2110207985","https://openalex.org/W2145453687","https://openalex.org/W2148721079","https://openalex.org/W2150588363","https://openalex.org/W2163274265","https://openalex.org/W2214429195","https://openalex.org/W2230472587","https://openalex.org/W2250630028","https://openalex.org/W2251079237","https://openalex.org/W2251135946","https://openalex.org/W2251670667","https://openalex.org/W2252136820","https://openalex.org/W2295522710","https://openalex.org/W2341824259","https://openalex.org/W2409591106","https://openalex.org/W2427527485","https://openalex.org/W2516930406","https://openalex.org/W2552027021","https://openalex.org/W2555025048","https://openalex.org/W2556691798","https://openalex.org/W2565031282","https://openalex.org/W2584341106","https://openalex.org/W2949117887","https://openalex.org/W2949776890","https://openalex.org/W2950133940","https://openalex.org/W2951008357","https://openalex.org/W2951534261","https://openalex.org/W2952155763","https://openalex.org/W2964121744","https://openalex.org/W2964224278","https://openalex.org/W2964267515"],"related_works":["https://openalex.org/W2252136820","https://openalex.org/W2251079237","https://openalex.org/W2094728533","https://openalex.org/W2409591106","https://openalex.org/W2131726681","https://openalex.org/W1981419611","https://openalex.org/W2964212344","https://openalex.org/W102708294","https://openalex.org/W580074167","https://openalex.org/W2591368218","https://openalex.org/W2022166150","https://openalex.org/W2341824259","https://openalex.org/W2573462507","https://openalex.org/W2908230750","https://openalex.org/W2896457183","https://openalex.org/W2572289264","https://openalex.org/W2250539671","https://openalex.org/W2250225488","https://openalex.org/W2090243146","https://openalex.org/W2080133951"],"abstract_inverted_index":{"Existing":[0],"question":[1,89,126,135],"answering":[2,23,127,136],"methods":[3,19],"infer":[4],"answers":[5],"either":[6,141],"from":[7,12],"a":[8,75,142],"knowledge":[9,16],"base":[10,17],"or":[11,144],"raw":[13],"text.":[14],"While":[15],"(KB)":[18],"are":[20,46],"good":[21],"at":[22],"compositional":[24],"questions,":[25],"their":[26],"performance":[27],"is":[28,137],"often":[29],"affected":[30],"by":[31,71,154],"the":[32,35,49,62,97,103,151],"incompleteness":[33],"of":[34,43,64,100,105],"KB.":[36,108],"Au":[37],"contraire,":[38],"web":[39],"text":[40,70,106,145],"contains":[41],"millions":[42],"facts":[44,101],"that":[45,130],"absent":[47],"in":[48,52,74,102,114],"KB,":[50],"however":[51],"an":[53,115],"unstructured":[54,69],"form.":[55],"Universal":[56],"schema":[57,85,133],"can":[58,111],"support":[59],"reasoning":[60],"on":[61,118,123],"union":[63],"both":[65],"structured":[66],"KBs":[67],"and":[68,107],"aligning":[72],"them":[73],"common":[76],"embedded":[77],"space.":[78],"In":[79],"this":[80],"paper":[81],"we":[82],"extend":[83],"universal":[84,132],"to":[86,94,96],"natural":[87],"language":[88],"answering,":[90],"employing":[91],"memory":[92],"networks":[93],"attend":[95],"large":[98],"body":[99],"combination":[104],"Our":[109],"models":[110],"be":[112],"trained":[113],"end-to-end":[116],"fashion":[117],"question-answer":[119],"pairs.":[120],"Evaluation":[121],"results":[122],"SPADES":[124],"fill-in-the-blank":[125],"dataset":[128],"show":[129],"exploiting":[131],"for":[134],"better":[138],"than":[139],"using":[140],"KB":[143],"alone.":[146],"This":[147],"model":[148],"also":[149],"outperforms":[150],"current":[152],"state-of-the-art":[153],"8.5":[155],"F":[156],"1":[157],"points.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
