Desambiguação lexical de sentidos para o português por meio de uma abordagem multilíngue mono e multidocumento

Abstract

The lexical ambiguity is considered one of the main barries to improving applications of Natural Language Processing (NLP). In this context, it has benn the area of Word Sense Disambiguation (WSD), whose goal is to develop and evaluate methods to determine the correct sense of a word in a give context by a nite set of possible meanings. The DLS is used mainly in order to provide resources and tools to reduce problems of ambiguity and thus contribute to improved results in other areas of NLP. In the Portuguese of Brazil, little has been researched in this area, with some work and speci c domain. Another important factor is that many areas of NLP commit themselves in multidocument scenario, where the computation is performed on a collection of texts, however, there is no report of WSD work directed to this scenario, either disambiguation experiments in this eld. Therefore, this master thesis aimed to develop methods of WSD general domain facing the Portuguese language in Brazil and the development of algorithms that make use of disambiguation multidocument informations, as well as experimentation and evaluation of the multidocument scenario. Therefore, in order to support experiments, development and evaluation of this project, the corpus CSTNews with 50 document collections, was manually annotated by means of synsets of the WordNet Princeton. Four methods were developed: A heuristic method (to measure values fo baseline); variations of the Lesk (1986) algorithm; a adaptation of the Mihalcea and Moldovan (1999) algorithm; and a variation of the Lesk method for multidocument scenario. Three experiments were conducted to evaluate the methods, whose objectives were to determine the general performance algorithms across the corpus; evaluate the quality of disambiguation of most ambiguous words in the corpus, and check the gain quality of disambiguation by employing information multidocumento. After these experiments, it was observed that the heuristic method presents a better overall result. However, it is important to note that most of the words in the annotated corpus had only one synset, which usually was the most frequent, which, in turn, presents a scenario more conducive to the heuristic method. Another important fact was that in this scenario, the performance di erence between the heuristic method and multidocument algorithm was statistically irrelevant. As for the disambiguation of most ambiguous words, the heuristic method was lower, indicating that, for the disambiguation of ambiguous words, more sophisticated WSD methods are needed. Finally, it has been found that the use of multidocument information assists the disambiguation process. The contributions of this work can be divided between theoretical and technical. In theory, there is the research and analysis of WSD in multidocument scenario. Among the techniques contributions, WSD methods have been developed an annotated corpus and annotation tool targeted to the Portuguese language in Brazil that can advance research in WSD for the language.