Laura Monceaux

French EuroWordNet Lexical Database Improvements

Semantic knowledge is often used in the framework of Natural Language Processing (NLP) applications. However, for some languages different from English, such knowledge is not always easily available. In fact, for example, French thesaurus are not numerous and are not enough developed. In this context, we present two modifications made on the French version of the EuroWordnet Thesaurus in order to improve it. Firstly, we present the French EuroWordNet thesaurus and its limits. Then we explain two improvements we have made. We add non-existing relationships by using the bilinguism capability of the EuroWordnet thesaurus, and definitions by using an external multilingual resource (Wikipedia [1]).

PEAS, the first instantiation of a comparative framework for evaluating parsers of French

This paper presents PEAS, the first comparative evaluation framework for parsers of French whose annotation formalism allows the annotation of both constituents and functional relations. A test corpus containing an assortment of different text types has been built and part of it has been manually annotated. Precision/Recall and crossing brackets metrics will be adapted to our formalism and applied to the parses produced by one parser from academia and another one from industry in order to validate the framework.

Coping With Alternate Formulations Of Questions And Answers

We present in this chapter the QALC system which has participated in the four TREC QA evaluations. We focus here on the problem of linguistic variation in order to be able to relate questions and answers. We present first, variation at the term level which consists in retrieving questions terms in document sentences even if morphologic, syntactic or semantic variations alter them. Our second subject matter concerns variation at the sentence level that we handle as different partial reformulations of questions. Questions are associated with extraction patterns based on the question syntactic type and the object that is under query. We present the whole system thus allowing situating how QALC deals with variation, and different evaluations.

The answer validation system ProdicosAV dedicated to French

In this paper, we present the ProdicosAV answer validation system which was developed by the NLP team from the LINA institute. ProdicosAV system is based on the Prodicos System which participated two years ago in the Question Answering CLEF evaluation campaign for French. We firstly present the modifications made on Prodicos to improve it and to adapt it to a new kind of exercise. We present in details the ranking passage module and the temporal validator module. Secondly, the answer-validation module dedicated to the AVE task is presented. Finally, the evaluation is put forward to justify the results obtained.

Answering french questions in english by exploiting results from several sources of information

Our bilingual QA system MUSCLEF, is based on QALC, the monolingual system with which we have participated in the previous TREC, where our best results were obtained when we combined the results of several searches. First, QALC searched a reliable document collection for answers, and second the WEB. We kept this strategy for CLEF, returning two runs. In the first one, we modified QALC so as to handle multilinguality by translating the terms identified in the question. In the second run, we combined the results of the first run with those obtained by first translating the question, then applying the full QALC strategy i.e. searching both the collection and the WEB. The final evaluation confirms the fact that the best results are obtained by combining different sources of information.