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21
An attempt to formalize word sense disambiguation: maximizing efficiency by minimizing computational costs
In: Revista española de lingüística aplicada, ISSN 0213-2028, Vol. 22, 2009, pags. 77-88 (2009)
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22
Bases de conocimiento multilíngües para el procesamiento semántico a gran escala ; Multilingual knowledge resources for wide–coverage semantic processing
Cuadros Oller, Montserrat; Rigau Claramunt, German. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2008
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23
Extracción de relaciones sintagmáticas de corpus anotados
Navarro Colorado, Borja; Moreno Monteagudo, Lorenza; Martínez-Barco, Patricio. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2006
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24
Authors
In: http://www.lsi.upc.edu/~nlp/meaning/documentation/3rdYear/WP6.17.pdf (2005)
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25
Un enfoque integrado para la desambiguación
Atserias Batalla, Jordi. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2005
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26
Annotating WordNet
In: DTIC (2004)
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27
Mapping WorldNet Senses to a Lexical Database of Verbs
In: DTIC (2001)
Abstract: This paper describes automatic techniques for mapping 9611 semantically classified English verbs to WordNet senses. The verbs were initially grouped into 491 semantic classes based on syntactic categories; they were then mapped into WordNet senses according to three pieces of information: (1) prior probability of WordNet senses; (2) semantic similarity of WordNet senses for verbs within the same category; and (3) probabilistic correlations between WordNet relationship and verb frame data. Our techniques make use of a training set of 1791 disambiguated entries representing 1442 verbs occurring in 167 of the categories. The best results achieved .58 recall and .72 precision, versus a lower bound of .38 recall and .62 precision for assigning the most frequently occurring WordNet sense, and an upper bound of .75 recall and .87 precision for human judgment. ; Sponsored in part under DARPA contract N66001-00-2-8910, PFF/PECASE Award IRI-9629108, and NSF grant EIA0130422. Additional report no. UMIACS-TR-2001-02.
Keyword: *DATA BASES; *ENGLISH LANGUAGE; *LEXICAL DATABASES; *LEXICOGRAPHY; *MAPPING; *VERBS; *WORD MAPPING; *WORDNET; AMBIGUITY; CORRELATION; FRAMES; FREQUENCY; Information Science; JUDGEMENT(PSYCHOLOGY); Linguistics; PRECISION; PROBABILITY; RECALL; SEMANTICS; SYNTAX; WORDS(LANGUAGE); WSD(WORD SENSE DISAMBIGUATION)
URL: http://www.dtic.mil/docs/citations/ADA458846
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA458846
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28
Word Sense Disambiguation Using Automatically Acquired Verbal Preferences
In: ftp://ftp.cogs.sussex.ac.uk/pub/users/dianam/senseval.ps (2000)
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29
H.: Semantic rule filtering for web-scale relation extraction
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
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30
Authors
In: http://www.lsi.upc.edu/~nlp/meaning/documentation/2onYear/D2.2.pdf
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31
H.: Semantic rule filtering for web-scale relation extraction
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
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32
ABSTRACT Long Tail in Weighted Lexical Networks
In: http://www.aclweb.org/anthology/W/W12/W12-5102.pdf
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33
Auto-Discovery of NVEF Word-Pairs in Chinese Abstract
In: http://www.aclclp.org.tw/rocling/2003/M09.pdf
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34
World Wide Web presents several.
In: http://www.softcomputing.net/jucs2013.pdf
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35
The UNED systems at SENSEVAL-2
In: http://aclweb.org/anthology-new/S/S01/S01-1018.pdf
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36
ABSTRACT Long Tail in Weighted Lexical Networks
In: http://www.lirmm.fr/~lafourcade/ML-biblio/COGALEX3/COGALEX2012-ML-v4.pdf
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37
USYD: WSD and Lexical Substitution using the Web1T Corpus Abstract This paper describes the University of Sydney’s WSD and Lexical Substitution systems
In: http://www.denizyuret.com/ref/hawker/98.pdf
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38
Development of an Approach for Disambiguating Ambiguous Hindi postposition
In: http://www.ijcaonline.org/volume5/number9/pxc3871317.pdf
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39
PARALLEL CORPORA, ALIGNMENT TECHNOLOGIES AND FURTHER PROSPECTS IN MULTILINGUAL RESOURCES AND TECHNOLOGY INFRASTRUCTURE
In: http://www.racai.ro/~tufis/papers/Tufis-Ion-SPED2007.pdf
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40
Addressing Challenges in Multilingual Machine Translation
In: http://www.ijser.org/researchpaper/Addressing_Challenges_in_Multilingual_Machine_Translation.pdf
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