{"id":"https://openalex.org/W4387903924","doi":"https://doi.org/10.1162/dint_a_00234","title":"A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense","display_name":"A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense","publication_year":2023,"publication_date":"2023-10-24","ids":{"openalex":"https://openalex.org/W4387903924","doi":"https://doi.org/10.1162/dint_a_00234"},"language":"en","primary_location":{"id":"doi:10.1162/dint_a_00234","is_oa":true,"landing_page_url":"https://doi.org/10.1162/dint_a_00234","pdf_url":"https://direct.mit.edu/dint/article-pdf/doi/10.1162/dint_a_00234/2163877/dint_a_00234.pdf","source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://direct.mit.edu/dint/article-pdf/doi/10.1162/dint_a_00234/2163877/dint_a_00234.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018837174","display_name":"Henrique Santos","orcid":"https://orcid.org/0000-0002-2110-6416"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Henrique Santos","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy NY","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066556597","display_name":"Ke Shen","orcid":"https://orcid.org/0000-0003-3600-0435"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ke Shen","raw_affiliation_strings":["Information Sciences Institute, Marina del Rey CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Sciences Institute, Marina del Rey CA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014146922","display_name":"Alice M. Mulvehill","orcid":null},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alice M. Mulvehill","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy NY","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074197492","display_name":"Mayank Kejriwal","orcid":"https://orcid.org/0000-0001-5988-8305"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mayank Kejriwal","raw_affiliation_strings":["Information Sciences Institute, Marina del Rey CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Sciences Institute, Marina del Rey CA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043699777","display_name":"Deborah L. McGuinness","orcid":"https://orcid.org/0000-0001-7037-4567"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deborah L. McGuinness","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy NY","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5863,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.86127706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9950000047683716,"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/T12031","display_name":"Speech and dialogue systems","score":0.9639999866485596,"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/common-sense","display_name":"Common sense","score":0.7505061030387878},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7471982836723328},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6995247006416321},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6837950944900513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6043785810470581},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5698570609092712},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45528990030288696},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.42301270365715027},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36899706721305847},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3137667179107666},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.10178986191749573}],"concepts":[{"id":"https://openalex.org/C2779814899","wikidata":"https://www.wikidata.org/wiki/Q332880","display_name":"Common sense","level":2,"score":0.7505061030387878},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7471982836723328},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6995247006416321},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6837950944900513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6043785810470581},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5698570609092712},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45528990030288696},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.42301270365715027},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36899706721305847},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3137667179107666},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.10178986191749573},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1162/dint_a_00234","is_oa":true,"landing_page_url":"https://doi.org/10.1162/dint_a_00234","pdf_url":"https://direct.mit.edu/dint/article-pdf/doi/10.1162/dint_a_00234/2163877/dint_a_00234.pdf","source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:261cdce2bec540a1b9847b7b358ddbad","is_oa":false,"landing_page_url":"https://doaj.org/article/261cdce2bec540a1b9847b7b358ddbad","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Intelligence (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1162/dint_a_00234","is_oa":true,"landing_page_url":"https://doi.org/10.1162/dint_a_00234","pdf_url":"https://direct.mit.edu/dint/article-pdf/doi/10.1162/dint_a_00234/2163877/dint_a_00234.pdf","source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G5865625667","display_name":null,"funder_award_id":"N660011924033","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":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4387903924.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W95183648","https://openalex.org/W2073302931","https://openalex.org/W2120534674","https://openalex.org/W2122540544","https://openalex.org/W2127833584","https://openalex.org/W2144427809","https://openalex.org/W2145755360","https://openalex.org/W2154611638","https://openalex.org/W2396767181","https://openalex.org/W2943552823","https://openalex.org/W2946609015","https://openalex.org/W2963101081","https://openalex.org/W2963196011","https://openalex.org/W2963341956","https://openalex.org/W2963995027","https://openalex.org/W2965373594","https://openalex.org/W2970062726","https://openalex.org/W2970597249","https://openalex.org/W2970780738","https://openalex.org/W2971236147","https://openalex.org/W2979669231","https://openalex.org/W2998617917","https://openalex.org/W3004346089","https://openalex.org/W3015759694","https://openalex.org/W3098008462","https://openalex.org/W3101056292","https://openalex.org/W3102999298","https://openalex.org/W3115951983","https://openalex.org/W3174496853","https://openalex.org/W3205068155","https://openalex.org/W3211511509","https://openalex.org/W3212464620","https://openalex.org/W3215367316","https://openalex.org/W3216256135","https://openalex.org/W4206125497","https://openalex.org/W4224279587","https://openalex.org/W4238525339","https://openalex.org/W4283800421","https://openalex.org/W4288089799","https://openalex.org/W4288262459","https://openalex.org/W4292779060","https://openalex.org/W4302305761","https://openalex.org/W4361205837","https://openalex.org/W4387903924","https://openalex.org/W4399762789","https://openalex.org/W6609703661"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W2922073769","https://openalex.org/W4378510483","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4221142204","https://openalex.org/W1492295194"],"abstract_inverted_index":{"ABSTRACT":[0],"Achieving":[1],"machine":[2],"common":[3,25,37,65,75,96,155],"sense":[4,26,38,76,156],"has":[5],"been":[6,43],"a":[7,22,69,81,92,110],"longstanding":[8],"problem":[9],"within":[10],"Artificial":[11],"Intelligence.":[12],"Thus":[13],"far,":[14],"benchmark":[15,105,148],"data":[16],"sets":[17],"that":[18,52,133],"are":[19,116],"grounded":[20,90],"in":[21,91,118],"theory":[23],"of":[24,36,47,83,95,126,159],"and":[27,102,113],"can":[28,55,149],"be":[29,150],"used":[30,151],"to":[31,122,143,152],"conduct":[32],"rigorous,":[33],"semantic":[34,93,145],"evaluations":[35,131],"reasoning":[39,157],"(CSR)":[40],"systems":[41,63],"have":[42],"lacking.":[44],"One":[45],"expectation":[46],"the":[48,119,124,154],"AI":[49],"community":[50],"is":[51,106,135],"neuro-symbolic":[53,160],"reasoners":[54],"help":[56],"bridge":[57],"this":[58,147],"gap":[59],"towards":[60],"more":[61],"dependable":[62],"with":[64,87],"sense.":[66],"We":[67],"propose":[68],"novel":[70],"benchmark,":[71],"called":[72],"Theoretically":[73],"Grounded":[74],"Reasoning":[77],"(TG-CSR),":[78],"modeled":[79],"as":[80,99],"set":[82],"question":[84],"answering":[85],"instances,":[86],"each":[88],"instance":[89],"category":[94],"sense,":[97],"such":[98],"space,":[100],"time,":[101],"emotions.":[103],"The":[104],"few-shot":[107],"i.e.,":[108],"only":[109],"few":[111],"training":[112],"validation":[114],"examples":[115],"provided":[117],"public":[120],"release":[121],"avoid":[123],"possibility":[125],"overfitting.":[127],"Results":[128],"from":[129],"recent":[130],"suggest":[132],"TG-CSR":[134],"challenging":[136],"even":[137],"for":[138],"state-of-the-art":[139],"statistical":[140],"models.":[141],"Due":[142],"its":[144],"rigor,":[146],"evaluate":[153],"capabilities":[158],"systems.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}