Xavier Blanco

A Survey of Multilingual Event Extraction from Text

The ability to process multilingual texts is important for the event extraction systems, because it not only completes the picture of an event, but also improves the algorithm performance quality. The present paper is a partial overview of the systems that cover this functionality. We focus on language-specific event type identification methods. Obtaining and organizing this knowledge is important for our further experiments on mono- and multilingual detection of socio-political events.

Constructing empirical models for automatic dialog parameterization

Automatic classification of dialogues between clients and a service center needs a preliminary dialogue parameterization. Such a parameterization is usually faced with essential difficulties when we deal with politeness, competence, satisfaction, and other similar characteristics of clients. In the paper, we show how to avoid these difficulties using empirical formulae based on lexical-grammatical properties of a text. Such formulae are trained on given set of examples, which are evaluated manually by an expert(s) and the best formula is selected by the Ivakhnenko Method of Model Self-Organization. We test the suggested methodology on the real set of dialogues from Barcelona railway directory inquiries for estimation of passengers politeness.

Testing Word Similarity: Language Independent Approach with Examples from Romance

Identification of words with the same basic meaning (stemming) has important applications in Information Retrieval, first of all for constructing word frequency lists. Usual morphologically-based approaches (including the Porter stemmers) rely on language-dependent linguistic resources or knowledge, which causes problems when working with multilingual data and multi-thematic document collections. We suggest several empirical formulae with easy to adjust parameters and demonstrate how to construct such formulae for a given language using an inductive method of model self-organization. This method considers a set of models (formulae) of a given class and selects the best ones using training and test samples. We describe the method and give detailed examples for French, Italian, Portuguese, and Spanish. The formulae are examined on real domain-oriented document collections. Our approach can be easily applied to other European languages.

A Modified Tripartite Model for Document Representation in Internet Sociology

Seven years ago Peter Mika (Yahoo! Research) proposed a tripartite model of actors, concepts and instances for document representation in the study of social networks. We propose a modified model, where instead of document authors we consider textual mentions of persons and institutions as actors. This representation proves to be more appropriate for the solution of a range of Internet Sociology tasks. In the paper we describe experiments with the modified model and provide some background on the tools that can be used to build it. The model is tested on the experimental corpora of Russian news (educational domain). The research reflects the pilot study findings.

A Hierarchy of Semantic Labels for Spanish Dictionaries

We present a hierarchy of semantic labels for the Spanish language. Each semantic label corresponds to the genus proximum (the next kind) of the lexical units that it describes. After having chosen ALGO ‘something’ as the head of our hierarchy, we distinguish between HECHO ‘fact’ and ENTIDAD ‘entity’, each of which are further partitioned into around twenty subclasses. Facts correspond to predicates while entities can correspond either to semantic names (objects) or to quasi-predicates. For disambiguation of predicates and quasi-predicates, we use the notion of an actantial formula (a linguistic expression that specifies the actants of a predicative form). The implementation of this hierarchy in the Spanish electronic dictionary of NooJ would allow us to foresee diverse applications.