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)
|
|
BASE
|
|
Show details
|
|
22 |
Bases de conocimiento multilíngües para el procesamiento semántico a gran escala ; Multilingual knowledge resources for wide–coverage semantic processing
|
|
|
|
BASE
|
|
Show details
|
|
24 |
Authors
|
|
|
|
In: http://www.lsi.upc.edu/~nlp/meaning/documentation/3rdYear/WP6.17.pdf (2005)
|
|
BASE
|
|
Show details
|
|
27 |
Mapping WorldNet Senses to a Lexical Database of Verbs
|
|
|
|
In: DTIC (2001)
|
|
BASE
|
|
Show details
|
|
28 |
Word Sense Disambiguation Using Automatically Acquired Verbal Preferences
|
|
|
|
In: ftp://ftp.cogs.sussex.ac.uk/pub/users/dianam/senseval.ps (2000)
|
|
BASE
|
|
Show details
|
|
29 |
H.: Semantic rule filtering for web-scale relation extraction
|
|
|
|
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
|
|
Abstract:
Abstract. Web-scale relation extraction is a means for building and extending large repositories of formalized knowledge. This type of automated knowledge building requires a decent level of precision, which is hard to achieve with au-tomatically acquired rule sets learned from unlabeled data by means of distant or minimal supervision. This paper shows how precision of relation extraction can be considerably improved by employing a wide-coverage, general-purpose lexical semantic network, i.e., BabelNet, for effective semantic rule filtering. We apply Word Sense Disambiguation to the content words of the automatically ex-tracted rules. As a result a set of relation-specific relevant concepts is obtained, and each of these concepts is then used to represent the structured semantics of the corresponding relation. The resulting relation-specific subgraphs of BabelNet are used as semantic filters for estimating the adequacy of the extracted rules. For the seven semantic relations tested here, the semantic filter consistently yields a higher precision at any relative recall value in the high-recall range.
|
|
Keyword:
Relation Extraction; Rule Filtering; Semantic relations; Semantics; Web-scale; WSD
|
|
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.644.1160 http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
|
|
BASE
|
|
Hide details
|
|
30 |
Authors
|
|
|
|
In: http://www.lsi.upc.edu/~nlp/meaning/documentation/2onYear/D2.2.pdf
|
|
BASE
|
|
Show details
|
|
31 |
H.: Semantic rule filtering for web-scale relation extraction
|
|
|
|
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
|
|
BASE
|
|
Show details
|
|
32 |
ABSTRACT Long Tail in Weighted Lexical Networks
|
|
|
|
In: http://www.aclweb.org/anthology/W/W12/W12-5102.pdf
|
|
BASE
|
|
Show details
|
|
33 |
Auto-Discovery of NVEF Word-Pairs in Chinese Abstract
|
|
|
|
In: http://www.aclclp.org.tw/rocling/2003/M09.pdf
|
|
BASE
|
|
Show details
|
|
34 |
World Wide Web presents several.
|
|
|
|
In: http://www.softcomputing.net/jucs2013.pdf
|
|
BASE
|
|
Show details
|
|
35 |
The UNED systems at SENSEVAL-2
|
|
|
|
In: http://aclweb.org/anthology-new/S/S01/S01-1018.pdf
|
|
BASE
|
|
Show details
|
|
36 |
ABSTRACT Long Tail in Weighted Lexical Networks
|
|
|
|
In: http://www.lirmm.fr/~lafourcade/ML-biblio/COGALEX3/COGALEX2012-ML-v4.pdf
|
|
BASE
|
|
Show details
|
|
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
|
|
BASE
|
|
Show details
|
|
38 |
Development of an Approach for Disambiguating Ambiguous Hindi postposition
|
|
|
|
In: http://www.ijcaonline.org/volume5/number9/pxc3871317.pdf
|
|
BASE
|
|
Show details
|
|
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
|
|
BASE
|
|
Show details
|
|
40 |
Addressing Challenges in Multilingual Machine Translation
|
|
|
|
In: http://www.ijser.org/researchpaper/Addressing_Challenges_in_Multilingual_Machine_Translation.pdf
|
|
BASE
|
|
Show details
|
|
|
|