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In this paper, an approach to semantic disambiguation based on machine learning and semantic classes for Spanish is presented. A critical issue in a corpus-based approach for Word Sense Disambiguation (WSD) is the lack of wide-coverage resources to automatically learn the linguistic information. In particular, all-words sense annotated corpora such as SemCor do not have enough examples for many senses when used in a machine learning method. Using semantic classes instead of senses allows to collect a larger number of examples for each class while polysemy is reduced, improving the accuracy of semantic disambiguation. Cast3LB, a SemCor-like corpus, manually annotated with Spanish WordNet 1.5 senses, has been used in this paper to perform semantic disambiguation based on several sets of classes: lexicographer files of WordNet, WordNet Domains, and SUMO ontology. [ABSTRACT FROM AUTHOR]

This paper describes the development of an image retrieval system that combines probabilistic and ontological informationThis work has been partially supported by the Spanish Government (CICYT) with grant TIC2003-07158-c04-01.. The process is divided in two different stages: indexing and retrieval. Three information flows have been created with different kind of information each one: word forms, stems and stemmed bigrams. The final result combines the results obtained in the three streams. Knowledge is added to the system by means of an ontology created automatically from the St. Andrews Corpus. The system has been evaluated at CLEF05 image retrieval task. [ABSTRACT FROM AUTHOR]

In this paper we discuss to what extent the choice of one particular Part-of-Speech (PoS) tagger determines the results obtained by a word sense disambiguation (WSD) system. We have chosen several PoS taggers and two WSD methods. By combining them, and using different kind of information, several experiments have been carried out. The WSD systems have been evaluated using the corpora of the lexical sample task of senseval-3 for English. The results show that some PoS taggers work better with one specific method. That is, selecting the right combination of these tools, could improve the results obtained by a WSD system. [ABSTRACT FROM AUTHOR]