{"id":"https://openalex.org/W2891308403","doi":"https://doi.org/10.48550/arxiv.1809.02922","title":"Transforming Question Answering Datasets Into Natural Language Inference Datasets","display_name":"Transforming Question Answering Datasets Into Natural Language Inference Datasets","publication_year":2018,"publication_date":"2018-09-09","ids":{"openalex":"https://openalex.org/W2891308403","doi":"https://doi.org/10.48550/arxiv.1809.02922","mag":"2891308403"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1809.02922","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.02922","pdf_url":"https://arxiv.org/pdf/1809.02922","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,"listed_in":[],"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"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.02922","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052171928","display_name":"Dorottya Demszky","orcid":"https://orcid.org/0000-0002-6759-9367","observed_orcids":["https://orcid.org/0000-0002-6759-9367"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Demszky, Dorottya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076669462","display_name":"Kelvin Guu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guu, Kelvin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025255782","display_name":"Percy Liang","orcid":"https://orcid.org/0000-0002-0458-6139","observed_orcids":["https://orcid.org/0000-0002-0458-6139"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Percy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":116,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.7997999787330627,"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":0.7997999787330627,"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":0.17980000376701355,"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":0.005900000222027302,"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/natural-language-inference","display_name":"natural language inference","score":0.9850000143051147},{"id":"https://openalex.org/keywords/question-answering-dataset","display_name":"question answering dataset","score":0.9179999828338623},{"id":"https://openalex.org/keywords/sentence-transformation","display_name":"sentence transformation","score":0.7850000262260437},{"id":"https://openalex.org/keywords/question-answer-pairs","display_name":"question-answer pairs","score":0.7049999833106995}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8502222299575806},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6969778537750244},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.687374472618103},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6832287907600403},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6830517053604126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6578078866004944},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5871129631996155},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4937964379787445},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.43984368443489075},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.43840524554252625},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:1809.02922","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.02922","pdf_url":"https://arxiv.org/pdf/1809.02922","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,"listed_in":[],"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":"doi:10.48550/arxiv.1809.02922","doi":"https://doi.org/10.48550/arxiv.1809.02922","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1809.02922","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,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1809.02922","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.02922","pdf_url":"https://arxiv.org/pdf/1809.02922","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,"listed_in":[],"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"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/4","score":0.8199999928474426,"display_name":"Quality education"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W806995027","https://openalex.org/W1522301498","https://openalex.org/W1828163288","https://openalex.org/W2125436846","https://openalex.org/W2126034021","https://openalex.org/W2143927888","https://openalex.org/W2250539671","https://openalex.org/W2250790822","https://openalex.org/W2411652523","https://openalex.org/W2427527485","https://openalex.org/W2515796212","https://openalex.org/W2557764419","https://openalex.org/W2594047108","https://openalex.org/W2606964149","https://openalex.org/W2607892599","https://openalex.org/W2612431505","https://openalex.org/W2612953412","https://openalex.org/W2613904329","https://openalex.org/W2626778328","https://openalex.org/W2739827909","https://openalex.org/W2763722198","https://openalex.org/W2771039833","https://openalex.org/W2771275742","https://openalex.org/W2788496822","https://openalex.org/W2790415926","https://openalex.org/W2950819771","https://openalex.org/W2953084091","https://openalex.org/W2963323070","https://openalex.org/W2963888305","https://openalex.org/W2964165364","https://openalex.org/W2964260331","https://openalex.org/W2964308564"],"related_works":["https://openalex.org/W3092461730","https://openalex.org/W3087063344","https://openalex.org/W4388825151","https://openalex.org/W2998107946","https://openalex.org/W7204283026","https://openalex.org/W7211920697","https://openalex.org/W4385574293","https://openalex.org/W4383340139","https://openalex.org/W4416035627","https://openalex.org/W2798284509"],"abstract_inverted_index":{"Existing":[0],"datasets":[1,22],"for":[2,18],"natural":[3],"language":[4,11],"inference":[5,99],"(NLI)":[6],"have":[7],"propelled":[8],"research":[9],"on":[10,35,53],"understanding.":[12],"We":[13],"propose":[14],"a":[15,37,54,67,79,95],"new":[16,80],"method":[17],"automatically":[19,77],"deriving":[20],"NLI":[21,87,105],"from":[23],"the":[24],"growing":[25],"abundance":[26],"of":[27,69,84,98],"large-scale":[28],"question":[29],"answering":[30],"datasets.":[31,106],"Our":[32],"approach":[33],"hinges":[34],"learning":[36],"sentence":[38],"transformation":[39],"model":[40],"which":[41],"converts":[42],"question-answer":[43],"pairs":[44],"into":[45],"their":[46],"declarative":[47],"forms.":[48],"Despite":[49],"being":[50],"primarily":[51],"trained":[52],"single":[55],"QA":[56,71],"dataset,":[57],"we":[58,76],"show":[59,91],"that":[60,92],"it":[61,93],"can":[62],"be":[63],"successfully":[64],"applied":[65],"to":[66],"variety":[68],"other":[70],"resources.":[72],"Using":[73],"this":[74],"system,":[75],"derive":[78],"freely":[81],"available":[82],"dataset":[83],"over":[85],"500k":[86],"examples":[88],"(QA-NLI),":[89],"and":[90],"exhibits":[94],"wide":[96],"range":[97],"phenomena":[100],"rarely":[101],"seen":[102],"in":[103],"previous":[104]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":30},{"year":2021,"cited_by_count":28},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2018-09-27T00:00:00"}
