Rubén Izquierdo

TL;DR: This paper presents QACID an ontology-based Question Answering system applied to the CInema Domain that allows users to retrieve information from formal ontologies by using as input queries formulated in natural language.

TL;DR: This paper presents the QALL-ME Framework, a reusable architecture for building multi- and cross-lingual Question Answering (QA) systems working on structured data modelled by an ontology, and presents a running example to clarify how the framework processes questions.

TL;DR: 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 the CLEF 2003 Spanish monolingual QA evaluation task are described.

TL;DR: A very simple method is used for deriving a small set of appropriate meanings using basic structural properties of WordNet and it is empirically demonstrated that this automatically derived set of meanings groups senses into an adequate level of abstraction in order to perform class-based Word Sense Disambiguation, allowing accuracy figures over 80%.

TL;DR: This study implemented a propagation algorithm and designed a method to obtain seed lists similar with respect to quality and size, for each of the five languages, and evaluated the results against gold standards also developed according to a common method in order to achieve as less variance as possible between the different languages.