In this paper we present the mapping between WordNet domains and WordNet topics, and the emergent Wikipedia categories. This mapping leads to a coarse alignment between WordNet and Wikipedia, useful for producing domain-specific and multilingual corpora. Multilinguality is achieved through the cross-language links between Wikipedia categories. Research in word-sense disambiguation has shown that within a specific domain, relevant words have restricted senses. The multilingual, and comparable, domain-specific corpora we produce have the potential to enhance research in word-sense disambiguation and terminology extraction in different languages, which could enhance the performance of various NLP tasks
Princeton WordNet is one of the most important resources for natural language processing, but is on...
This paper describes the automatic creation of semantic networks from Wikipedia. Following Lipczak e...
In this chapter, we explore how to develop and encode the relationship between wordnets for differen...
In this paper we present an automatic multilingual annotation of the Wikipedia dumps in two language...
Domain terms are a useful mean for tuning both resources and NLP processors to domain specific tasks...
Lexical resource differ from encyclopaedic resources and represent two distinct types of resource co...
Lexical knowledge bases (LKBs), such as WordNet, have been shown to be useful for a range of languag...
In this paper, we address the issue of automatic extending lexical resources by exploiting existing ...
We present three approaches to word sense disambiguation that use Wikipedia as a source of sense ann...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
This article presents a new freely available trilingual corpus (Catalan, Spanish, English) that cont...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
This article presents a new freely available trilingual corpus (Catalan, Spanish, English) that cont...
Princeton WordNet is one of the most important resources for natural language processing, but is onl...
The automatic development of semantic resources constitutes an important challenge in the NLP commun...
Princeton WordNet is one of the most important resources for natural language processing, but is on...
This paper describes the automatic creation of semantic networks from Wikipedia. Following Lipczak e...
In this chapter, we explore how to develop and encode the relationship between wordnets for differen...
In this paper we present an automatic multilingual annotation of the Wikipedia dumps in two language...
Domain terms are a useful mean for tuning both resources and NLP processors to domain specific tasks...
Lexical resource differ from encyclopaedic resources and represent two distinct types of resource co...
Lexical knowledge bases (LKBs), such as WordNet, have been shown to be useful for a range of languag...
In this paper, we address the issue of automatic extending lexical resources by exploiting existing ...
We present three approaches to word sense disambiguation that use Wikipedia as a source of sense ann...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
This article presents a new freely available trilingual corpus (Catalan, Spanish, English) that cont...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
This article presents a new freely available trilingual corpus (Catalan, Spanish, English) that cont...
Princeton WordNet is one of the most important resources for natural language processing, but is onl...
The automatic development of semantic resources constitutes an important challenge in the NLP commun...
Princeton WordNet is one of the most important resources for natural language processing, but is on...
This paper describes the automatic creation of semantic networks from Wikipedia. Following Lipczak e...
In this chapter, we explore how to develop and encode the relationship between wordnets for differen...