{"id":"https://openalex.org/W2889699743","doi":"https://doi.org/10.18653/v1/d18-1008","title":"Textual Analogy Parsing: What\u2019s Shared and What\u2019s Compared among Analogous Facts","display_name":"Textual Analogy Parsing: What\u2019s Shared and What\u2019s Compared among Analogous Facts","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2889699743","doi":"https://doi.org/10.18653/v1/d18-1008","mag":"2889699743"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1008","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1008","pdf_url":"https://www.aclweb.org/anthology/D18-1008.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1008.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005471354","display_name":"Matthew Lamm","orcid":null},"institutions":[{"id":"https://openalex.org/I1344076864","display_name":"Center for Applied Linguistics","ror":"https://ror.org/020pekv35","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1344076864"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Matthew Lamm","raw_affiliation_strings":["Stanford Linguistics","Stanford NLP Group"],"affiliations":[{"raw_affiliation_string":"Stanford Linguistics","institution_ids":["https://openalex.org/I1344076864"]},{"raw_affiliation_string":"Stanford NLP Group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024150057","display_name":"Arun Tejasvi Chaganty","orcid":"https://orcid.org/0000-0001-7122-1298"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arun Chaganty","raw_affiliation_strings":["Stanford Computer Science","Stanford NLP Group"],"affiliations":[{"raw_affiliation_string":"Stanford Computer Science","institution_ids":[]},{"raw_affiliation_string":"Stanford NLP Group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046006076","display_name":"Christopher D. Manning","orcid":"https://orcid.org/0000-0001-6155-649X"},"institutions":[{"id":"https://openalex.org/I1344076864","display_name":"Center for Applied Linguistics","ror":"https://ror.org/020pekv35","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1344076864"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher D. Manning","raw_affiliation_strings":["Stanford NLP Group","Stanford Linguistics","Stanford Computer Science"],"affiliations":[{"raw_affiliation_string":"Stanford NLP Group","institution_ids":[]},{"raw_affiliation_string":"Stanford Linguistics","institution_ids":["https://openalex.org/I1344076864"]},{"raw_affiliation_string":"Stanford Computer Science","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087088138","display_name":"Dan Jurafsky","orcid":"https://orcid.org/0000-0002-6459-7745"},"institutions":[{"id":"https://openalex.org/I1344076864","display_name":"Center for Applied Linguistics","ror":"https://ror.org/020pekv35","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1344076864"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Jurafsky","raw_affiliation_strings":["Stanford Computer Science","Stanford NLP Group","Stanford Linguistics"],"affiliations":[{"raw_affiliation_string":"Stanford Computer Science","institution_ids":[]},{"raw_affiliation_string":"Stanford NLP Group","institution_ids":[]},{"raw_affiliation_string":"Stanford Linguistics","institution_ids":["https://openalex.org/I1344076864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025255782","display_name":"Percy Liang","orcid":"https://orcid.org/0000-0002-0458-6139"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Percy Liang","raw_affiliation_strings":["Stanford Computer Science","Stanford NLP Group"],"affiliations":[{"raw_affiliation_string":"Stanford Computer Science","institution_ids":[]},{"raw_affiliation_string":"Stanford NLP Group","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5005471354"],"corresponding_institution_ids":["https://openalex.org/I1344076864"],"apc_list":null,"apc_paid":null,"fwci":1.858,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.89151062,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"82","last_page":"92"},"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":0.9994000196456909,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9790999889373779,"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/parsing","display_name":"Parsing","score":0.7814527750015259},{"id":"https://openalex.org/keywords/meaning","display_name":"Meaning (existential)","score":0.7138967514038086},{"id":"https://openalex.org/keywords/analogy","display_name":"Analogy","score":0.70548015832901},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6135334968566895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6026054620742798},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5958090424537659},{"id":"https://openalex.org/keywords/poverty","display_name":"Poverty","score":0.5597335696220398},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.540340781211853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.513552188873291},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4843924641609192},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.4450405240058899},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.43548956513404846},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2553458511829376},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.12418746948242188},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.07154911756515503}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7814527750015259},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.7138967514038086},{"id":"https://openalex.org/C521332185","wikidata":"https://www.wikidata.org/wiki/Q185816","display_name":"Analogy","level":2,"score":0.70548015832901},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6135334968566895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6026054620742798},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5958090424537659},{"id":"https://openalex.org/C189326681","wikidata":"https://www.wikidata.org/wiki/Q10294","display_name":"Poverty","level":2,"score":0.5597335696220398},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.540340781211853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.513552188873291},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4843924641609192},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.4450405240058899},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.43548956513404846},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2553458511829376},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.12418746948242188},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.07154911756515503},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1008","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1008","pdf_url":"https://www.aclweb.org/anthology/D18-1008.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1008","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1008","pdf_url":"https://www.aclweb.org/anthology/D18-1008.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.8100000023841858,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2889699743.pdf","grobid_xml":"https://content.openalex.org/works/W2889699743.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1539746312","https://openalex.org/W1566346388","https://openalex.org/W1581597064","https://openalex.org/W1586232984","https://openalex.org/W1592033656","https://openalex.org/W1832693441","https://openalex.org/W1990100773","https://openalex.org/W1994335990","https://openalex.org/W2027429247","https://openalex.org/W2039336675","https://openalex.org/W2098844768","https://openalex.org/W2109462987","https://openalex.org/W2115792525","https://openalex.org/W2118450042","https://openalex.org/W2123442489","https://openalex.org/W2137640092","https://openalex.org/W2141599568","https://openalex.org/W2145454741","https://openalex.org/W2146432541","https://openalex.org/W2147880316","https://openalex.org/W2151170651","https://openalex.org/W2158847908","https://openalex.org/W2250539671","https://openalex.org/W2251349042","https://openalex.org/W2251599843","https://openalex.org/W2252016937","https://openalex.org/W2296283641","https://openalex.org/W2396804222","https://openalex.org/W2397198482","https://openalex.org/W2406675876","https://openalex.org/W2565515778","https://openalex.org/W2625237928","https://openalex.org/W2740765036","https://openalex.org/W2899771611","https://openalex.org/W2913389685","https://openalex.org/W2915085887","https://openalex.org/W2962769333","https://openalex.org/W2964222246","https://openalex.org/W3099021111","https://openalex.org/W4213168938","https://openalex.org/W4234473045","https://openalex.org/W4241881032","https://openalex.org/W4244729909"],"related_works":["https://openalex.org/W2392206215","https://openalex.org/W2365201483","https://openalex.org/W2355561779","https://openalex.org/W2352407775","https://openalex.org/W2469799552","https://openalex.org/W108701362","https://openalex.org/W2615704157","https://openalex.org/W176509374","https://openalex.org/W28964973","https://openalex.org/W46969452"],"abstract_inverted_index":{"To":[0],"understand":[1],"a":[2,73,104,126,133],"sentence":[3,159],"like":[4],"\"whereas":[5],"only":[6,27],"10%":[7,96],"of":[8,19,35,58,70,145],"White":[9,91],"Americans":[10,21,92],"live":[11],"at":[12],"or":[13],"below":[14],"the":[15,41,47,56,142,146,157],"poverty":[16,33,84],"line,":[17],"28%":[18],"African":[20,94],"do\"":[22],"it":[23],"is":[24,72,81,88],"important":[25],"not":[26],"to":[28,63,140],"identify":[29],"individual":[30],"facts,":[31],"e.g.,":[32,46],"rates":[34],"distinct":[36],"demographic":[37],"groups,":[38],"but":[39],"also":[40],"higher-order":[42,66],"relations":[43],"between":[44,49,99],"them,":[45],"disparity":[48],"them.":[50],"In":[51],"this":[52,65],"paper,":[53],"we":[54],"propose":[55],"task":[57],"Textual":[59],"Analogy":[60],"Parsing":[61],"(TAP)":[62],"model":[64,134],"meaning.":[67],"The":[68],"output":[69],"TAP":[71],"frame-style":[74],"meaning":[75,105],"representation":[76,106],"which":[77],"explicitly":[78],"specifies":[79],"what":[80,87],"shared":[82],"(e.g.,":[83,90],"rates)":[85],"and":[86,132,156],"compared":[89],"vs.":[93,97],"Americans,":[95],"28%)":[98],"its":[100],"component":[101],"facts.":[102],"Such":[103],"can":[107],"enable":[108],"new":[109,127],"applications":[110],"that":[111,135],"rely":[112],"on":[113],"discourse":[114],"understanding":[115],"such":[116],"as":[117],"automated":[118],"chart":[119],"generation":[120],"from":[121,160],"quantitative":[122],"text.":[123],"We":[124],"present":[125],"dataset":[128],"for":[129],"TAP,":[130],"baselines,":[131],"successfully":[136],"uses":[137],"an":[138],"ILP":[139],"enforce":[141],"structural":[143],"constraints":[144],"problem.":[147],"*":[148],"Author":[149],"contributed":[150],"significantly.":[151],"1":[152],"Data":[153],"in":[154],"E1":[155],"figure":[158],"Morris":[161],"(2014).":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4}],"updated_date":"2026-03-07T13:37:22.277990","created_date":"2025-10-10T00:00:00"}
