Tiago


2006

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COMBINA-PT: A Large Corpus-extracted and Hand-checked Lexical Database of Portuguese Multiword Expressions
Amália Mendes | Sandra Antunes | Maria Fernanda Bacelar do Nascimento | João Miguel Casteleiro | Luísa Pereira | Tiago Sá
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

This paper presents the COMBINA-PT project, a study of corpus-extracted Portuguese Multiword (MW) expressions. The objective of this on-going project is to compile a large lexical database of multiword (MW) units of the Portuguese language, automatically extracted from a balanced 50 million word corpus, and manually validated with the help of lexical association measures. MW expressions considered in the database include named entities and lexical associations with different degrees of cohesion, ranging from frozen groups, which undergo little or no variation, to lexical collocations composed of words that tend to occur together and that constitute syntactic dependencies, although with a low degree of fixedness. This new resource has a two-fold objective: (i) to be an important research tool which supports the development of MW expressions typologies and their lexicographic treatment; (ii) to be of major help in developing and evaluating language processing tools able of dealing with MW expressions.

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Corpus-based extraction and identification of Portuguese Multiword Expressions
Sandra Antunes | Maria Fernanda Bacelar do Nascimento | João Miguel Casteleiro | Amália Mendes | Luísa Pereira | Tiago Sá
Actes de la 13ème conférence sur le Traitement Automatique des Langues Naturelles. Posters

This presentation reports on an on-going project aimed at building a large lexical database of corpus-extracted multiword (MW) expressions for the Portuguese language. MW expressions were automatically extracted from a balanced 50 million word corpus compiled for this project, furthermore these were statistically interpreted using lexical association measures, followed by a manual validation process. The lexical database covers different types of MW expressions, from named entities to lexical associations with different degrees of cohesion, ranging from totally frozen idioms to favoured co-occurring forms, such as collocations. We aim to achieve two main objectives with this resource. Firstly to build on the large set of data of different types of MW expressions, thus revising existing typologies of collocations and integrating them in a larger theory of MW units. Secondly, to use the extensive hand-checked data as training data to evaluate existing statistical lexical association measures.