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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 cou-rant. 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 ré-cupérées. 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)
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)
In this paper we argue that question-answering (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)
Logic-based answer extraction techniques present a solution to retrieve and mark those exact passages in a document that directly answer a natural language query. In contrast to pure information retrieval techniques that treat content words as isolated terms, answer extraction techniques exploit syntactic information in a document to a certain degree and(More)
Question answering on speech transcripts (QAst) is a pilot track of the CLEF competition. In this paper we present our contribution to QAst, which 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. We have ported AFNER, the NE recogniser of the AnswerFinder(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 gram-maire utilisés sacrifient le fonctionnalisme (dans le cadre des grammaires de dépendance) au profit de la projectivité. Nous avons(More)
Named Entity Recognisers (NERs) are typically used by question answering (QA) systems as means to preselect answer candidates. However, there has not been much work on the formal assessment of the use of NERs for QA nor on their optimal parameters. In this paper we investigate the main characteristics of a NER for QA. The results show that it is important(More)