Diego Mollá

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Les systèmes d’Extraction de Réponses (ER) récupèrent dans des documents des expressions qui répondent directement à des questions du langage courant. L’ER pour des manuels techniques exige un haut niveau de rappel et de précision ; pourtant, ce sont de petites unités de texte qui doivent être récupérées. C’est pourquoi il est important d’effectuer une(More)
Current text-based question answering (QA) systems usually contain a named entity recogniser (NER) as a core component. Named entity recognition has traditionally been developed as a component for information extraction systems, and current techniques are focused on this end use. However, no formal assessment has been done on the characteristics of a NER(More)
Nous exposons ici l’implémentation d’un système d’extraction de réponses, ExtrAns, qui utilise la sortie d’un analyseur et d’une grammaire basés sur les dépendances. Afin d’augmenter la vitesse de calcul, l’analyseur et la grammaire utilisés sacrifient le fonctionnalisme (dans le cadre des grammaires de dépendance) au profit de la projectivité. Nous avons(More)
In this paper we argue that questionanswering (QA) over technical domains is distinctly different from TREC-based QA or Web-based QA and it cannot benefit from data-intensive approaches. Technical questions arise in situations where concrete problems require specific answers and explanations. Finding a justification of the answer in the context of the(More)
We present a question answering system that combines information at the lexical, syntactic, and semantic levels, in the process to find and rank the candidate answer sentences. The candidate exact answers are extracted from the candidate answer sentences by means of a combination of information-extraction techniques (named entity recognition) and patterns(More)
Our contribution is centred on a study of Named Entity (NE) recognition on speech transcripts and how it impacts on the accuracy of the final question answering system. AnswerFinder was adapted to the task of question answering on speech transcripts and participated in the QAst pilot track of the CLEF competition. We have ported AFNER, the NE recogniser of(More)