Rubén Izquierdo

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This paper describes the architecture, operation and results obtained with the Question Answering prototype for Spanish developed in the Department of Language Processing and Information Systems at the University of Alicante for CLEF-2003 Spanish monolingual QA evaluation task. Our system has been fully developed from scratch and it combines shallow natural(More)
This paper presents QACID an ontology-based Question Answering system applied to the CInema Domain. This system allows users to retrieve information from formal ontologies by using as input queries formulated in natural language. The original characteristic of QACID is the strategy used to fill the gap between users’ expressiveness and formal knowledge(More)
This paper presents the QALL-ME Framework, a reusable architecture for building multiand cross-lingual Question Answering (QA) systems working on structured data modelled by an ontology. It is released as free open source software with a set of demo components and extensive documentation, which makes it easy to use and adapt. The main characteristics of the(More)
We present a very simple method for selecting Base Level Concepts using some basic structural properties of WordNet. We also empirically demonstrate that these automatically derived set of Base Level Concepts group senses into an adequate level of abstraction in order to perform class-based Word Sense Disambiguation. In fact, a very naive Most Frequent(More)
This paper describes the architecture, operation and results obtained with the Question Answering prototype for Spanish developed in the Department of Language Processing and Information Systems at the University of Alicante for CLEF-2004 Spanish monolingual QA evaluation task. Our system is based on the prototype developed for CLEF-2003 Spanish monolingual(More)
This paper describes the novelties introduced in the Question Answering system developed in the Natural Language Processing and Information Systems Group at the University of Alicante for QA@CLEF 2005 campaign with respect to our previous participations. Thinking of future developments, this year we have designed a modular framework based on XML that will(More)
As empirically demonstrated by the last SensEval exercises, assigning the appropriate meaning to words in context has resisted all attempts to be successfully addressed. One possible reason could be the use of inappropriate set of meanings. In fact, WordNet has been used as a de-facto standard repository of meanings. However, to our knowledge, the meanings(More)
Word Sense Disambiguation (WSD) systems require large sense-tagged corpora along with lexical databases to reach satisfactory results. The number of English language resources for developed WSD increased in the past years while most other languages are still under-resourced. The situation is no different for Dutch. In order to overcome this data bottleneck,(More)
This paper describes the participation of the University of Alicante (UA) in CLEF 2005 image retrieval task. For this purpose we used an image retrieval system based on probabilistic information combined with ontological information and a feedback technique. Several information streams are created using different sources: stems, words and bigrams; the final(More)
We present a very simple method for selecting Base Level Concepts using basic structural properties of WordNet. We also empirically demonstrate that these automatically derived set of Base Level Concepts group senses into an adequate level of abstraction in order to perform class-based Word Sense Disambiguation. In fact a very naive Most Frequent classifier(More)