{"id":"https://openalex.org/W2963101081","doi":"https://doi.org/10.1609/aaai.v33i01.33013027","title":"ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning","display_name":"ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2963101081","doi":"https://doi.org/10.1609/aaai.v33i01.33013027","mag":"2963101081"},"language":"en","primary_location":{"id":"pmh:oai:ojs.aaai.org:article/4160","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4160","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/publishedVersion"},"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015128745","display_name":"Maarten Sap","orcid":"https://orcid.org/0000-0002-0701-4654"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sap, Maarten","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024879161","display_name":"Ronan Le Bras","orcid":"https://orcid.org/0000-0003-2439-6938"},"institutions":[{"id":"https://openalex.org/I4210140341","display_name":"Allen Institute","ror":"https://ror.org/03cpe7c52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Le Bras, Ronan","raw_affiliation_strings":["Allen Institute for AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Allen Institute for AI","institution_ids":["https://openalex.org/I4210140341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008920438","display_name":"Emily Allaway","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Allaway, Emily","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044250030","display_name":"Chandra Bhagavatula","orcid":"https://orcid.org/0000-0001-6264-0378"},"institutions":[{"id":"https://openalex.org/I4210140341","display_name":"Allen Institute","ror":"https://ror.org/03cpe7c52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhagavatula, Chandra","raw_affiliation_strings":["Allen Institute for AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Allen Institute for AI","institution_ids":["https://openalex.org/I4210140341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029809608","display_name":"Nicholas Lourie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140341","display_name":"Allen Institute","ror":"https://ror.org/03cpe7c52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lourie, Nicholas","raw_affiliation_strings":["Allen Institute for AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Allen Institute for AI","institution_ids":["https://openalex.org/I4210140341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076412680","display_name":"Hannah Rashkin","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rashkin, Hannah","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009034593","display_name":"Brendan Roof","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140341","display_name":"Allen Institute","ror":"https://ror.org/03cpe7c52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roof, Brendan","raw_affiliation_strings":["Allen Institute for AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Allen Institute for AI","institution_ids":["https://openalex.org/I4210140341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088517824","display_name":"Noah A. Smith","orcid":"https://orcid.org/0000-0002-2310-6380"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Smith, Noah A.","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102992157","display_name":"Yejin Choi","orcid":"https://orcid.org/0000-0003-3032-5378"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Choi, Yejin","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":60.1614,"has_fulltext":true,"cited_by_count":741,"citation_normalized_percentile":{"value":0.9989434,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"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":0.983299970626831,"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":0.983299970626831,"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":0.9822999835014343,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.688113808631897},{"id":"https://openalex.org/keywords/commonsense-knowledge","display_name":"Commonsense knowledge","score":0.6598220467567444},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.6175592541694641},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5820769667625427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5767098069190979},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.49138393998146057},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4636211693286896},{"id":"https://openalex.org/keywords/atlas","display_name":"Atlas (anatomy)","score":0.44000840187072754},{"id":"https://openalex.org/keywords/isolation","display_name":"Isolation (microbiology)","score":0.4140954911708832},{"id":"https://openalex.org/keywords/cognitive-science","display_name":"Cognitive science","score":0.3420111835002899},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.33618080615997314},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.32782065868377686},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.21305415034294128},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.09736710786819458}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.688113808631897},{"id":"https://openalex.org/C30542707","wikidata":"https://www.wikidata.org/wiki/Q1603203","display_name":"Commonsense knowledge","level":3,"score":0.6598220467567444},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.6175592541694641},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5820769667625427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5767098069190979},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.49138393998146057},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4636211693286896},{"id":"https://openalex.org/C2776673561","wikidata":"https://www.wikidata.org/wiki/Q655357","display_name":"Atlas (anatomy)","level":2,"score":0.44000840187072754},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.4140954911708832},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.3420111835002899},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.33618080615997314},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.32782065868377686},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.21305415034294128},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.09736710786819458},{"id":"https://openalex.org/C89423630","wikidata":"https://www.wikidata.org/wiki/Q7193","display_name":"Microbiology","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:ojs.aaai.org:article/4160","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4160","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/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1219216712","display_name":"III: Medium: Learning Multimodal Knowledge about Entities and Events","funder_award_id":"1703166","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2099617666","display_name":null,"funder_award_id":"1256082","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3943856530","display_name":null,"funder_award_id":"DGE-1256082","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5310676827","display_name":"RI: Small: A Data-Driven Framework to Sketch-to-Text Generation","funder_award_id":"1524371","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5385673730","display_name":null,"funder_award_id":"W911NF-15-1-","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G5551313627","display_name":"RI: Small: ConnotationNet: Modeling Non-Literal Meaning in Context","funder_award_id":"1714566","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8257659198","display_name":null,"funder_award_id":"W911NF-15","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"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"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"},{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1525578932","https://openalex.org/W1533230146","https://openalex.org/W1819170319","https://openalex.org/W1950324769","https://openalex.org/W2050482109","https://openalex.org/W2073302931","https://openalex.org/W2143177362","https://openalex.org/W2145755360","https://openalex.org/W2147638277","https://openalex.org/W2151295812","https://openalex.org/W2250539671","https://openalex.org/W2250770256","https://openalex.org/W2250837944","https://openalex.org/W2335559472","https://openalex.org/W2466175319","https://openalex.org/W2561529111","https://openalex.org/W2592393750","https://openalex.org/W2740432174","https://openalex.org/W2748533788","https://openalex.org/W2791297471","https://openalex.org/W2962739339","https://openalex.org/W2962781380","https://openalex.org/W2963305465","https://openalex.org/W2963691697","https://openalex.org/W2963903950","https://openalex.org/W2964199361","https://openalex.org/W4297730339"],"related_works":["https://openalex.org/W3035583586","https://openalex.org/W4320165839","https://openalex.org/W2151799802","https://openalex.org/W4386607580","https://openalex.org/W4385488510","https://openalex.org/W2196562041","https://openalex.org/W2073302931","https://openalex.org/W4378501473","https://openalex.org/W3082691151","https://openalex.org/W4287633646"],"abstract_inverted_index":{"We":[0,52],"present":[1],"ATOMIC,":[2,85],"an":[3],"atlas":[4],"of":[5,14,113],"everyday":[6],"commonsense":[7,94],"reasoning,":[8],"organized":[9,31],"through":[10],"877k":[11],"textual":[12],"descriptions":[13],"inferential":[15,29,81],"knowledge.":[16],"Compared":[17],"to":[18,58,118,123],"existing":[19],"resources":[20],"that":[21,88,105,108],"center":[22],"around":[23],"taxonomic":[24],"knowledge,":[25],"ATOMIC":[26],"focuses":[27],"on":[28,78],"knowledge":[30,82],"as":[32,128],"typed":[33],"if-then":[34,55,114],"relations":[35],"with":[36],"variables":[37],"(e.g.,":[38],"\u201cif":[39],"X":[40],"pays":[41],"Y":[42,46],"a":[43],"compliment,":[44],"then":[45],"will":[47],"likely":[48],"return":[49],"the":[50,79,110],"compliment\u201d).":[51],"propose":[53],"nine":[54],"relation":[56,115],"types":[57,116],"distinguish":[59],"causes":[60],"vs.":[61,64,67,72],"effects,":[62],"agents":[63],"themes,":[65],"voluntary":[66],"involuntary":[68],"events,":[69],"and":[70,96,133],"actions":[71],"mental":[73],"states.":[74],"By":[75],"generatively":[76],"training":[77],"rich":[80],"described":[83],"in":[84,126],"we":[86],"show":[87],"neural":[89],"models":[90,107,124],"can":[91],"acquire":[92],"simple":[93],"capabilities":[95],"reason":[97],"about":[98],"previously":[99],"unseen":[100],"events.":[101],"Experimental":[102],"results":[103],"demonstrate":[104],"multitask":[106],"incorporate":[109],"hierarchical":[111],"structure":[112],"lead":[117],"more":[119],"accurate":[120],"inference":[121],"compared":[122],"trained":[125],"isolation,":[127],"measured":[129],"by":[130],"both":[131],"automatic":[132],"human":[134],"evaluation.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":67},{"year":2024,"cited_by_count":95},{"year":2023,"cited_by_count":156},{"year":2022,"cited_by_count":135},{"year":2021,"cited_by_count":139},{"year":2020,"cited_by_count":105},{"year":2019,"cited_by_count":36}],"updated_date":"2026-06-18T10:00:31.954636","created_date":"2025-10-10T00:00:00"}
