{"id":"https://openalex.org/W2252269235","doi":"https://doi.org/10.18653/v1/d15-1114","title":"Mise en Place: Unsupervised Interpretation of Instructional Recipes","display_name":"Mise en Place: Unsupervised Interpretation of Instructional Recipes","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2252269235","doi":"https://doi.org/10.18653/v1/d15-1114","mag":"2252269235"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d15-1114","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1114","pdf_url":"https://www.aclweb.org/anthology/D15-1114.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 2015 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/D15-1114.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065231138","display_name":"Chlo\u00e9 Kiddon","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":true,"raw_author_name":"Chlo\u00e9 Kiddon","raw_affiliation_strings":["Computer Science & Engineering, University of Washington, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of Washington, Seattle, WA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086845698","display_name":"Ganesa Thandavam Ponnuraj","orcid":null},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ganesa Thandavam Ponnuraj","raw_affiliation_strings":["Department of Computer Science, Stony Brook University, Stony Brook, NY"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Stony Brook University, Stony Brook, NY","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067919401","display_name":"Luke Zettlemoyer","orcid":"https://orcid.org/0009-0008-8296-0764"},"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":"Luke Zettlemoyer","raw_affiliation_strings":["Computer Science & Engineering, University of Washington, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of Washington, Seattle, WA","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":"Yejin Choi","raw_affiliation_strings":["Computer Science & Engineering, University of Washington, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of Washington, Seattle, WA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065231138"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":12.0186,"has_fulltext":true,"cited_by_count":101,"citation_normalized_percentile":{"value":0.985155,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"982","last_page":"992"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9957000017166138,"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":0.6675640940666199},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.6579405069351196},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4383181631565094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3969985842704773},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.14751270413398743}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6675640940666199},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.6579405069351196},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4383181631565094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3969985842704773},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.14751270413398743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d15-1114","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1114","pdf_url":"https://www.aclweb.org/anthology/D15-1114.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 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d15-1114","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1114","pdf_url":"https://www.aclweb.org/anthology/D15-1114.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 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8600000143051147,"display_name":"Quality Education"}],"awards":[{"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/G6497436218","display_name":"CAREER: Learning Scalable Models for Grounded Semantic Parsing","funder_award_id":"1252835","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320952","display_name":"International Science and Technology Center","ror":"https://ror.org/03fn1w943"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2252269235.pdf","grobid_xml":"https://content.openalex.org/works/W2252269235.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W71776421","https://openalex.org/W158164316","https://openalex.org/W1602500555","https://openalex.org/W1740041947","https://openalex.org/W1988912276","https://openalex.org/W2000900121","https://openalex.org/W2006969979","https://openalex.org/W2047493830","https://openalex.org/W2081580037","https://openalex.org/W2103210555","https://openalex.org/W2111078031","https://openalex.org/W2111692356","https://openalex.org/W2118781169","https://openalex.org/W2122223050","https://openalex.org/W2132986783","https://openalex.org/W2143797800","https://openalex.org/W2145374219","https://openalex.org/W2156047221","https://openalex.org/W2158794898","https://openalex.org/W2164585080","https://openalex.org/W2181626422","https://openalex.org/W2189089430","https://openalex.org/W2215946058","https://openalex.org/W2250379752","https://openalex.org/W2250965435","https://openalex.org/W2251927492","https://openalex.org/W2252052418","https://openalex.org/W2252139350","https://openalex.org/W2252840007","https://openalex.org/W2598334070","https://openalex.org/W2922052901","https://openalex.org/W2964040984","https://openalex.org/W4247735228","https://openalex.org/W4386506836"],"related_works":["https://openalex.org/W2789919619","https://openalex.org/W2293457016","https://openalex.org/W3169305685","https://openalex.org/W2351428524","https://openalex.org/W1551406738","https://openalex.org/W2610387714","https://openalex.org/W2369308426","https://openalex.org/W1569841287","https://openalex.org/W1512718085","https://openalex.org/W2359001871"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2],"unsupervised":[3],"hard":[4],"EM":[5],"approach":[6],"to":[7,12,36,91],"automatically":[8],"mapping":[9],"instructional":[10],"recipes":[11,87],"action":[13,95],"graphs,":[14,96],"which":[15,23],"define":[16],"what":[17,27],"actions":[18],"should":[19],"be":[20,33,53],"performed":[21],"on":[22],"objects":[24],"and":[25,57,71,78],"in":[26,105],"order.":[28],"Recovering":[29],"such":[30,74],"structures":[31],"can":[32,52],"challenging,":[34],"due":[35],"unique":[37],"properties":[38],"of":[39,68],"procedural":[40,69],"language":[41],"where,":[42],"for":[43,81],"example,":[44],"verbal":[45],"arguments":[46],"are":[47],"commonly":[48],"elided":[49],"when":[50],"they":[51],"inferred":[54],"from":[55],"context":[56],"disambiguation":[58],"often":[59],"requires":[60],"world":[61,72],"knowledge.":[62],"Our":[63],"probabilistic":[64],"model":[65],"incorporates":[66],"aspects":[67],"semantics":[70],"knowledge,":[73],"as":[75],"likely":[76],"locations":[77],"selectional":[79],"preferences":[80],"different":[82],"actions.":[83],"Experiments":[84],"with":[85],"cooking":[86],"demonstrate":[88],"the":[89],"ability":[90],"recover":[92],"high":[93],"quality":[94],"outperforming":[97],"a":[98],"strong":[99],"sequential":[100],"baseline":[101],"by":[102],"8":[103],"points":[104],"F1,":[106],"while":[107],"also":[108],"discovering":[109],"general-purpose":[110],"knowledge":[111],"about":[112],"cooking.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":4}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
