{"id":"https://openalex.org/W2165401052","doi":"https://doi.org/10.1017/s1351324904003328","title":"Towards automatic fine-grained semantic classification of verb-noun collocations","display_name":"Towards automatic fine-grained semantic classification of verb-noun collocations","publication_year":2004,"publication_date":"2004-05-13","ids":{"openalex":"https://openalex.org/W2165401052","doi":"https://doi.org/10.1017/s1351324904003328","mag":"2165401052"},"language":"en","primary_location":{"id":"doi:10.1017/s1351324904003328","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324904003328","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5087323271","display_name":"Leo Wanner","orcid":"https://orcid.org/0000-0002-9446-3748"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"LEO WANNER","raw_affiliation_strings":["Computer Science Department, University of Stuttgart, Universit\u00e4tsstr. 38, 70569 Stuttgart, Germany e-mail:"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Stuttgart, Universit\u00e4tsstr. 38, 70569 Stuttgart, Germany e-mail:","institution_ids":["https://openalex.org/I100066346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5087323271"],"corresponding_institution_ids":["https://openalex.org/I100066346"],"apc_list":null,"apc_paid":null,"fwci":4.0473,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.94070785,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"10","issue":"2","first_page":"95","last_page":"143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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":1.0,"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":0.9958000183105469,"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/T12353","display_name":"Lexicography and Language Studies","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8601517677307129},{"id":"https://openalex.org/keywords/bigram","display_name":"Bigram","score":0.8303701877593994},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7497351765632629},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.710249662399292},{"id":"https://openalex.org/keywords/verb","display_name":"Verb","score":0.6116504073143005},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.5290122628211975},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.46979960799217224},{"id":"https://openalex.org/keywords/collocation","display_name":"Collocation (remote sensing)","score":0.46694910526275635},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.45676732063293457},{"id":"https://openalex.org/keywords/trigram","display_name":"Trigram","score":0.07497268915176392}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8601517677307129},{"id":"https://openalex.org/C108757681","wikidata":"https://www.wikidata.org/wiki/Q2773912","display_name":"Bigram","level":3,"score":0.8303701877593994},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7497351765632629},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.710249662399292},{"id":"https://openalex.org/C2776397901","wikidata":"https://www.wikidata.org/wiki/Q24905","display_name":"Verb","level":2,"score":0.6116504073143005},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.5290122628211975},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.46979960799217224},{"id":"https://openalex.org/C80023036","wikidata":"https://www.wikidata.org/wiki/Q5147531","display_name":"Collocation (remote sensing)","level":2,"score":0.46694910526275635},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.45676732063293457},{"id":"https://openalex.org/C137546455","wikidata":"https://www.wikidata.org/wiki/Q3213474","display_name":"Trigram","level":2,"score":0.07497268915176392},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s1351324904003328","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324904003328","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7699999809265137,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W32302389","https://openalex.org/W33087893","https://openalex.org/W164621428","https://openalex.org/W203027767","https://openalex.org/W1482448220","https://openalex.org/W1516391399","https://openalex.org/W1561693360","https://openalex.org/W1563714358","https://openalex.org/W1566745747","https://openalex.org/W1585054724","https://openalex.org/W1596967103","https://openalex.org/W1659833910","https://openalex.org/W1735182246","https://openalex.org/W1754931551","https://openalex.org/W1938444495","https://openalex.org/W1940278502","https://openalex.org/W1973532090","https://openalex.org/W1986348501","https://openalex.org/W2020505496","https://openalex.org/W2033152911","https://openalex.org/W2038721957","https://openalex.org/W2044070623","https://openalex.org/W2063993968","https://openalex.org/W2067882062","https://openalex.org/W2072208512","https://openalex.org/W2075645124","https://openalex.org/W2154767329","https://openalex.org/W2158243292","https://openalex.org/W2158652440","https://openalex.org/W2159637323","https://openalex.org/W2166391512","https://openalex.org/W2245946358","https://openalex.org/W2534712034","https://openalex.org/W2549253258","https://openalex.org/W2561822374","https://openalex.org/W2950225692"],"related_works":["https://openalex.org/W2378425157","https://openalex.org/W2543455653","https://openalex.org/W2101702282","https://openalex.org/W2381229644","https://openalex.org/W2361754849","https://openalex.org/W2376574096","https://openalex.org/W2762447962","https://openalex.org/W3119431074","https://openalex.org/W2602782736","https://openalex.org/W4220744014"],"abstract_inverted_index":{"Plain":[0],"lists":[1],"of":[2,14,35,55,65,82,91,101,125,134,149,159,176,186,193,227],"collocations":[3,15,67,92,102],"as":[4,20,38,68],"provided":[5,208],"to":[6,11,78,86,174,182,217],"date":[7],"by":[8,49,60,209],"most":[9],"approaches":[10],"automatic":[12],"acquisition":[13],"from":[16,116,137,204],"corpora":[17],"are":[18,171,202],"useful":[19],"a":[21,79,87,177],"resource":[22],"for":[23],"dictionary":[24],"construction.":[25],"However,":[26],"their":[27],"use":[28],"is":[29,107,180],"rather":[30],"limited":[31],"in":[32],"the":[33,52,56,63,66,117,122,126,128,131,141,146,157,161,195,199,205,210,213,219],"case":[34],"NLP-applications":[36],"such":[37],"Text":[39,44],"Generation,":[40],"Machine":[41],"Translation":[42],"and":[43,59,93,153,198],"Summarization":[45],"if":[46],"not":[47],"enriched":[48],"information":[50,61],"on":[51,62,109],"grammatical":[53],"function":[54],"collocation":[57],"elements":[58],"semantics":[64],"multiword":[69],"units.":[70],"In":[71,121,140,212],"this":[72,95,187],"article,":[73],"we":[74,221],"describe":[75],"an":[76,184,223],"approach":[77],"fine-grained":[80],"classification":[81,106],"verb-noun":[83,110,150],"bigrams":[84,152,201],"according":[85],"semantically":[88],"motivated":[89],"typology":[90,100],"illustrate":[94],"with":[96,156],"Spanish":[97],"material.":[98],"The":[99,190],"that":[103],"underlies":[104],"our":[105],"based":[108],"Lexical":[111],"Functions":[112],"(":[113],"LF":[114,136,162,179,188],"s)":[115],"Explanatory":[118],"Combinatorial":[119],"Lexicology.":[120],"first":[123],"stage":[124],"approach,":[127,220],"program":[129],"learns":[130],"semantic":[132,147,191],"features":[133,148,158,170,192],"each":[135],"training":[138,196],"data.":[139],"second":[142],"stage,":[143],"it":[144],"examines":[145],"candidate":[151,168,200],"compares":[154],"them":[155],"all":[160],"s":[163],"taken":[164],"into":[165],"account.":[166],"A":[167],"whose":[169],"sufficiently":[172],"similar":[173],"those":[175],"specific":[178],"considered":[181],"be":[183],"instance":[185],".":[189],"both":[194],"material":[197],"derived":[203],"hyperonymy":[206],"hierarchies":[207],"EuroWordNet.":[211],"experiments":[214],"carried":[215],"out":[216],"validate":[218],"achieved":[222],"average":[224],"$f$":[225],"-score":[226],"about":[228],"70%.":[229]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}