{"id":"https://openalex.org/W2460814443","doi":"https://doi.org/10.18653/v1/w16-1605","title":"Functional Distributional Semantics","display_name":"Functional Distributional Semantics","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2460814443","doi":"https://doi.org/10.18653/v1/w16-1605","mag":"2460814443"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w16-1605","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1605","pdf_url":"https://www.aclweb.org/anthology/W16-1605.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 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W16-1605.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041079942","display_name":"Guy Emerson","orcid":"https://orcid.org/0000-0002-3136-9682"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]},{"id":"https://openalex.org/I4210096386","display_name":"Bridge University","ror":"https://ror.org/00cbm0437","country_code":"SS","type":"education","lineage":["https://openalex.org/I4210096386"]}],"countries":["GB","SS"],"is_corresponding":true,"raw_author_name":"Guy Emerson","raw_affiliation_strings":["Computer Laboratory University of Cambridge","Univ. of Cambridge"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Laboratory University of Cambridge","institution_ids":["https://openalex.org/I4210096386","https://openalex.org/I241749"]},{"raw_affiliation_string":"Univ. of Cambridge","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012396877","display_name":"Ann Copestake","orcid":"https://orcid.org/0000-0003-0347-946X"},"institutions":[{"id":"https://openalex.org/I4210096386","display_name":"Bridge University","ror":"https://ror.org/00cbm0437","country_code":"SS","type":"education","lineage":["https://openalex.org/I4210096386"]},{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB","SS"],"is_corresponding":false,"raw_author_name":"Ann Copestake","raw_affiliation_strings":["Computer Laboratory University of Cambridge","University of Cambridge, Cambridge, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Laboratory University of Cambridge","institution_ids":["https://openalex.org/I4210096386","https://openalex.org/I241749"]},{"raw_affiliation_string":"University of Cambridge, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041079942"],"corresponding_institution_ids":["https://openalex.org/I241749","https://openalex.org/I4210096386"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03463764,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"40","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9975000023841858,"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":0.9943000078201294,"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":0.7857357859611511},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7082074284553528},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6288072466850281},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.615090548992157},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6092892289161682},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5843496918678284},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4791778326034546},{"id":"https://openalex.org/keywords/distributional-semantics","display_name":"Distributional semantics","score":0.4670727849006653},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4617732763290405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43655872344970703},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.3857503831386566},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.17303261160850525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7857357859611511},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7082074284553528},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6288072466850281},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.615090548992157},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6092892289161682},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5843496918678284},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4791778326034546},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.4670727849006653},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4617732763290405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43655872344970703},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.3857503831386566},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.17303261160850525},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.18653/v1/w16-1605","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1605","pdf_url":"https://www.aclweb.org/anthology/W16-1605.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 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1606.08003","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1606.08003","pdf_url":"https://arxiv.org/pdf/1606.08003","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2460814443","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1606.08003.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:www.repository.cam.ac.uk:1810/261866","is_oa":true,"landing_page_url":"https://www.repository.cam.ac.uk/handle/1810/261866","pdf_url":null,"source":{"id":"https://openalex.org/S4306401777","display_name":"Apollo (University of Cambridge)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I241749","host_organization_name":"University of Cambridge","host_organization_lineage":["https://openalex.org/I241749"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Object"},{"id":"doi:10.48550/arxiv.1606.08003","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1606.08003","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.17863/cam.7097","is_oa":true,"landing_page_url":"https://doi.org/10.17863/cam.7097","pdf_url":null,"source":{"id":"https://openalex.org/S7407050737","display_name":"Apollo","issn_l":null,"issn":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.18653/v1/w16-1605","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1605","pdf_url":"https://www.aclweb.org/anthology/W16-1605.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 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2460814443.pdf","grobid_xml":"https://content.openalex.org/works/W2460814443.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W125545343","https://openalex.org/W138379559","https://openalex.org/W168564468","https://openalex.org/W170175252","https://openalex.org/W224572144","https://openalex.org/W810147176","https://openalex.org/W1500718495","https://openalex.org/W1521626219","https://openalex.org/W1574467785","https://openalex.org/W1662133657","https://openalex.org/W1687416839","https://openalex.org/W1796264214","https://openalex.org/W1813659000","https://openalex.org/W1880262756","https://openalex.org/W1973942085","https://openalex.org/W1977970897","https://openalex.org/W1980491396","https://openalex.org/W2001722583","https://openalex.org/W2007871210","https://openalex.org/W2019599312","https://openalex.org/W2046609227","https://openalex.org/W2056760934","https://openalex.org/W2064148932","https://openalex.org/W2067438047","https://openalex.org/W2085574295","https://openalex.org/W2113517401","https://openalex.org/W2116825644","https://openalex.org/W2125031621","https://openalex.org/W2136922672","https://openalex.org/W2138309709","https://openalex.org/W2140610559","https://openalex.org/W2143252279","https://openalex.org/W2146502635","https://openalex.org/W2152444902","https://openalex.org/W2170682101","https://openalex.org/W2189408051","https://openalex.org/W2200913422","https://openalex.org/W2251762914","https://openalex.org/W2277323063","https://openalex.org/W2343872880","https://openalex.org/W2345905986","https://openalex.org/W2465321302","https://openalex.org/W2507113859","https://openalex.org/W2950577311","https://openalex.org/W2952300142","https://openalex.org/W2962796133","https://openalex.org/W2962813108","https://openalex.org/W2963869850","https://openalex.org/W3214201242"],"related_works":["https://openalex.org/W2950176964","https://openalex.org/W2250715854","https://openalex.org/W4828744","https://openalex.org/W2400957619","https://openalex.org/W3123279312","https://openalex.org/W2187268138","https://openalex.org/W2110721658","https://openalex.org/W2970812694","https://openalex.org/W1516892340","https://openalex.org/W2778392606","https://openalex.org/W2952811074","https://openalex.org/W3023344385","https://openalex.org/W3163322517","https://openalex.org/W2950996938","https://openalex.org/W2402552536","https://openalex.org/W2996686709","https://openalex.org/W3105588714","https://openalex.org/W2520227251","https://openalex.org/W1971866038","https://openalex.org/W2471720752"],"abstract_inverted_index":{"Vector":[0],"space":[1],"models":[2],"have":[3],"become":[4],"popular":[5],"in":[6,14,34],"distributional":[7],"semantics,":[8],"despite":[9],"the":[10,43,79],"challenges":[11],"they":[12,45],"face":[13],"capturing":[15],"various":[16],"semantic":[17],"phenomena.":[18],"We":[19,58],"propose":[20],"a":[21,66,88],"novel":[22],"probabilistic":[23],"framework":[24,64],"which":[25],"draws":[26],"on":[27,55,87,94],"both":[28],"formal":[29],"semantics":[30],"and":[31,72,91],"recent":[32],"advances":[33],"machine":[35],"learning.":[36],"In":[37],"particular,":[38],"we":[39,77],"separate":[40],"predicates":[41],"from":[42],"entities":[44],"refer":[46],"to,":[47],"allowing":[48],"us":[49],"to":[50],"perform":[51],"Bayesian":[52],"inference":[53],"based":[54],"logical":[56],"forms.":[57],"describe":[59],"an":[60],"implementation":[61],"of":[62,68,81],"this":[63,82],"using":[65],"combination":[67],"Restricted":[69],"Boltzmann":[70],"Machines":[71],"feedforward":[73],"neural":[74],"networks.":[75],"Finally,":[76],"demonstrate":[78],"feasibility":[80],"approach":[83],"by":[84],"training":[85],"it":[86,93],"parsed":[89],"corpus":[90],"evaluating":[92],"established":[95],"similarity":[96],"datasets.":[97]},"counts_by_year":[],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}