{"id":"https://openalex.org/W1758600199","doi":null,"title":"On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics","display_name":"On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1758600199","mag":"1758600199"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.902.9974","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.902.9974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.utexas.edu/users/ai-lab/downloadPublication.php?filename%3Dhttp%3A//www.cs.utexas.edu/users/ml/papers/beltagy.iwcs15.pdf%26pubid%3D127493","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"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/A5059172050","display_name":"Islam Beltagy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Islam Beltagy","raw_affiliation_strings":["University of Texas at Austin#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Austin#TAB#","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067235438","display_name":"Katrin Erk","orcid":"https://orcid.org/0000-0002-2888-6961","observed_orcids":["https://orcid.org/0000-0002-2888-6961"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katrin Erk","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-2888-6961","affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1789,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81846368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"140","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.6942999958992004,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.6942999958992004,"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":0.24580000340938568,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.014800000004470348,"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/probabilistic-logic","display_name":"probabilistic logic","score":0.9319999814033508},{"id":"https://openalex.org/keywords/quantifiers","display_name":"quantifiers","score":0.7960000038146973},{"id":"https://openalex.org/keywords/natural-language-inference","display_name":"natural language inference","score":0.8650000095367432},{"id":"https://openalex.org/keywords/closed-world-assumption","display_name":"closed world assumption","score":0.968999981880188},{"id":"https://openalex.org/keywords/natural-language-semantics","display_name":"natural language semantics","score":0.7829999923706055},{"id":"https://openalex.org/keywords/fracas","display_name":"FRACAS","score":0.5509999990463257},{"id":"https://openalex.org/keywords/first-order-logic","display_name":"first-order logic","score":0.5400000214576721}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7524107098579407},{"id":"https://openalex.org/C128828806","wikidata":"https://www.wikidata.org/wiki/Q7246848","display_name":"Probabilistic argumentation","level":3,"score":0.7512149214744568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.681292712688446},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.6208425164222717},{"id":"https://openalex.org/C18998212","wikidata":"https://www.wikidata.org/wiki/Q7246856","display_name":"Probabilistic logic network","level":5,"score":0.5880882143974304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5635386109352112},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.515596330165863},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5155025124549866},{"id":"https://openalex.org/C102993220","wikidata":"https://www.wikidata.org/wiki/Q387196","display_name":"Description logic","level":2,"score":0.49657803773880005},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4922007620334625},{"id":"https://openalex.org/C95318506","wikidata":"https://www.wikidata.org/wiki/Q6588467","display_name":"Textual entailment","level":3,"score":0.4690924882888794},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46649882197380066},{"id":"https://openalex.org/C146834321","wikidata":"https://www.wikidata.org/wiki/Q2979672","display_name":"Closure (psychology)","level":2,"score":0.44847792387008667},{"id":"https://openalex.org/C52063229","wikidata":"https://www.wikidata.org/wiki/Q7246845","display_name":"Probabilistic CTL","level":4,"score":0.4430617094039917},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41943755745887756},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33954763412475586},{"id":"https://openalex.org/C203659156","wikidata":"https://www.wikidata.org/wiki/Q6934805","display_name":"Multimodal logic","level":3,"score":0.30136147141456604},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2240014374256134},{"id":"https://openalex.org/C3845977","wikidata":"https://www.wikidata.org/wiki/Q4826262","display_name":"Autoepistemic logic","level":4,"score":0.21980604529380798},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2003856897354126},{"id":"https://openalex.org/C24404364","wikidata":"https://www.wikidata.org/wiki/Q7246846","display_name":"Probabilistic analysis of algorithms","level":3,"score":0.16369813680648804},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.902.9974","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.902.9974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.utexas.edu/users/ai-lab/downloadPublication.php?filename%3Dhttp%3A//www.cs.utexas.edu/users/ml/papers/beltagy.iwcs15.pdf%26pubid%3D127493","raw_type":"text"},{"id":"mag:1758600199","doi":null,"is_oa":false,"landing_page_url":"https://aclanthology.org/W15-0119/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1510929985","https://openalex.org/W1585529040","https://openalex.org/W1965605789","https://openalex.org/W1977970897","https://openalex.org/W1986069434","https://openalex.org/W2012170877","https://openalex.org/W2033194278","https://openalex.org/W2066770300","https://openalex.org/W2075322664","https://openalex.org/W2087451659","https://openalex.org/W2112576450","https://openalex.org/W2122702954","https://openalex.org/W2143252279","https://openalex.org/W2152084932","https://openalex.org/W2154474435","https://openalex.org/W2160052288","https://openalex.org/W2168652246","https://openalex.org/W2212090080","https://openalex.org/W2250748818","https://openalex.org/W2250790822","https://openalex.org/W2251044566","https://openalex.org/W2251673953","https://openalex.org/W2251861449","https://openalex.org/W2251898422","https://openalex.org/W2252136820","https://openalex.org/W2914728526"],"related_works":["https://openalex.org/W2552564118","https://openalex.org/W7101226001","https://openalex.org/W7098163169","https://openalex.org/W7042629054","https://openalex.org/W2337059180","https://openalex.org/W1924229470","https://openalex.org/W7098619492","https://openalex.org/W7014798923","https://openalex.org/W2295046466","https://openalex.org/W7098919856"],"abstract_inverted_index":{"As":[0],"a":[1,27,37,46,57,63,98,120,124],"format":[2],"for":[3],"describing":[4],"the":[5,14,20,49,75,102,148,158,163],"meaning":[6],"of":[7,16,129,166],"natural":[8,137,150],"language":[9],"sentences,":[10],"probabilistic":[11,32,95],"logic":[12,18,33,50,96],"com-bines":[13],"expressivity":[15],"first-order":[17],"with":[19,123],"ability":[21],"to":[22,45,71,87,145],"handle":[23],"graded":[24],"information":[25],"in":[26,40,48,74,94,97],"principled":[28],"fashion.":[29],"But":[30],"practical":[31],"frameworks":[34],"usually":[35],"assume":[36,56],"finite":[38],"domain":[39,103],"which":[41],"each":[42],"entity":[43],"corresponds":[44],"constant":[47],"(domain":[51],"closure":[52,104],"assumption).":[53],"They":[54],"also":[55],"closed":[58],"world":[59],"where":[60],"everything":[61],"has":[62],"very":[64],"low":[65],"prior":[66],"probability.":[67],"These":[68],"assumptions":[69,107],"lead":[70],"some":[72],"problems":[73,93],"inferences":[76],"that":[77,100,141],"these":[78],"systems":[79],"make.":[80],"In":[81],"this":[82],"paper,":[83],"we":[84],"show":[85,140],"how":[86],"formulate":[88],"Textual":[89],"Entail-ment":[90],"(RTE)":[91],"inference":[92],"way":[99],"takes":[101],"and":[105,133,152,161],"closed-world":[106],"into":[108],"account.":[109],"We":[110,139],"evaluate":[111],"our":[112,142],"proposed":[113],"technique":[114,143],"on":[115,119,126,131,134,147,157,162],"three":[116],"RTE":[117],"datasets,":[118],"synthetic":[121,159],"dataset":[122,160],"focus":[125],"complex":[127],"forms":[128],"quantification,":[130],"FraCas":[132],"one":[135],"more":[136,149],"dataset.":[138],"leads":[144],"improvements":[146],"dataset,":[151],"achieves":[153],"100":[154],"%":[155],"accuracy":[156],"relevant":[164],"part":[165],"FraCas.":[167],"1":[168]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}