{"id":"https://openalex.org/W2963895422","doi":"https://doi.org/10.1609/aaai.v33i01.33017208","title":"Improving Natural Language Inference Using External Knowledge in the Science Questions Domain","display_name":"Improving Natural Language Inference Using External Knowledge in the Science Questions Domain","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2963895422","doi":"https://doi.org/10.1609/aaai.v33i01.33017208","mag":"2963895422"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33017208","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017208","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4705/4583","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4705/4583","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100381772","display_name":"Xiaoyan Wang","orcid":"https://orcid.org/0000-0001-7997-8025"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoyan Wang","raw_affiliation_strings":["University of Illinois at Urbana-Champaign"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003720552","display_name":"Pavan Kapanipathi","orcid":"https://orcid.org/0000-0003-0494-3279"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pavan Kapanipathi","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086070288","display_name":"Ryan Musa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ryan Musa","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101583277","display_name":"Mo Yu","orcid":"https://orcid.org/0000-0003-0949-6113"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mo Yu","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060691179","display_name":"Kartik Talamadupula","orcid":"https://orcid.org/0000-0002-4628-3785"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kartik Talamadupula","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031546123","display_name":"Ibrahim Abdelaziz","orcid":"https://orcid.org/0000-0003-1449-5115"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ibrahim Abdelaziz","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102090109","display_name":"Maria Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maria Chang","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062643837","display_name":"Achille Fokoue","orcid":"https://orcid.org/0000-0003-1137-1344"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Achille Fokoue","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035662829","display_name":"Bassem Makni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bassem Makni","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025297787","display_name":"Nicholas Mattei","orcid":"https://orcid.org/0000-0002-3569-4335"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nicholas Mattei","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057995059","display_name":"Michael Witbrock","orcid":"https://orcid.org/0000-0002-7554-0971"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Witbrock","raw_affiliation_strings":["IBM Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":149,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"01","first_page":"7208","last_page":"7215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9797999858856201,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9743000268936157,"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/computer-science","display_name":"Computer science","score":0.8033862709999084},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6495206356048584},{"id":"https://openalex.org/keywords/premise","display_name":"Premise","score":0.6460662484169006},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.6167480945587158},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5566909313201904},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5508782267570496},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.4674195945262909},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.46692726016044617},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4616014361381531},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4365873336791992},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15631330013275146},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.13772660493850708},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07535925507545471}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8033862709999084},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6495206356048584},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.6460662484169006},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.6167480945587158},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5566909313201904},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5508782267570496},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4674195945262909},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.46692726016044617},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4616014361381531},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4365873336791992},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15631330013275146},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.13772660493850708},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07535925507545471},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33017208","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017208","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4705/4583","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/4705","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33017208","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017208","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4705/4583","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963895422.pdf","grobid_xml":"https://content.openalex.org/works/W2963895422.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W102708294","https://openalex.org/W1840435438","https://openalex.org/W2016089260","https://openalex.org/W2078446268","https://openalex.org/W2157082519","https://openalex.org/W2228826686","https://openalex.org/W2251869843","https://openalex.org/W2283196293","https://openalex.org/W2341381586","https://openalex.org/W2413794162","https://openalex.org/W2432356473","https://openalex.org/W2547185913","https://openalex.org/W2551396370","https://openalex.org/W2561529111","https://openalex.org/W2579563823","https://openalex.org/W2587019100","https://openalex.org/W2593833795","https://openalex.org/W2607892599","https://openalex.org/W2738674657","https://openalex.org/W2769395616","https://openalex.org/W2782838038","https://openalex.org/W2788496822","https://openalex.org/W2798416089","https://openalex.org/W2798665661","https://openalex.org/W2798760246","https://openalex.org/W2806507179","https://openalex.org/W2890961898","https://openalex.org/W2949523712","https://openalex.org/W2962958286","https://openalex.org/W2963091133","https://openalex.org/W2963123047","https://openalex.org/W2963249435","https://openalex.org/W2963542836","https://openalex.org/W2963846996","https://openalex.org/W2964294651","https://openalex.org/W4386506836","https://openalex.org/W6604189946","https://openalex.org/W7074675592"],"related_works":["https://openalex.org/W2388631242","https://openalex.org/W2122362795","https://openalex.org/W4245599380","https://openalex.org/W207673802","https://openalex.org/W2357796999","https://openalex.org/W2367925007","https://openalex.org/W3015724364","https://openalex.org/W4288263119","https://openalex.org/W2967994095","https://openalex.org/W2900126711"],"abstract_inverted_index":{"Natural":[0,8],"Language":[1,9],"Inference":[2],"(NLI)":[3],"is":[4,61],"fundamental":[5],"to":[6,27,37,52,65,131,166,175],"many":[7,98],"Processing":[10],"(NLP)":[11],"applications":[12],"including":[13],"semantic":[14],"search":[15],"and":[16,154,158],"question":[17],"answering.":[18],"The":[19],"NLI":[20,93,112,136,169,179],"problem":[21,39,137],"has":[22,86,113],"gained":[23],"significant":[24],"attention":[25,90],"due":[26],"the":[28,38,70,92,135,139,145,160,168,181],"release":[29],"of":[30,72,106,125,147,162],"large":[31],"scale,":[32],"challenging":[33],"datasets.":[34],"Present":[35],"approaches":[36],"largely":[40],"focus":[41],"on":[42,75,134,151,180],"learning-based":[43],"methods":[44,73],"that":[45,102,127],"use":[46,71,110],"only":[47],"textual":[48],"information":[49],"in":[50,82,138],"order":[51],"classify":[53],"whether":[54],"a":[55,66,79,123],"given":[56,67],"premise":[57],"entails,":[58],"contradicts,":[59],"or":[60],"neutral":[62],"with":[63],"respect":[64],"hypothesis.":[68],"Surprisingly,":[69],"based":[74,156],"structured":[76],"knowledge":[77,100,130,165],"\u2013":[78,85],"central":[80],"topic":[81],"artificial":[83],"intelligence":[84],"not":[87,114],"received":[88],"much":[89],"vis-a-vis":[91],"problem.":[94,170],"While":[95],"there":[96],"are":[97],"open":[99],"bases":[101],"contain":[103],"various":[104],"types":[105],"reasoning":[107],"information,":[108],"their":[109],"for":[111,178],"been":[115],"well":[116],"explored.":[117],"To":[118],"address":[119],"this,":[120],"we":[121],"present":[122,144],"combination":[124],"techniques":[126,150],"harness":[128],"external":[129,164],"improve":[132],"performance":[133,177],"science":[140,183],"questions":[141,184],"domain.":[142],"We":[143],"results":[146],"applying":[148],"our":[149],"text,":[152],"graph,":[153],"text-and-graph":[155],"models;":[157],"discuss":[159],"implications":[161],"using":[163],"solve":[167],"Our":[171],"model":[172],"achieves":[173],"close":[174],"state-of-the-art":[176],"SciTail":[182],"dataset.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":28},{"year":2020,"cited_by_count":30},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
