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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)
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)
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 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)
In this paper we motivate the need for a corpus for the development and testing of summarisation systems for evidence-based medicine. We describe the corpus which we are currently creating, and show its applicability by evaluating several simple query-based summarisation techniques using a small fragment of the corpus.
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)
This paper presents an overview of the 7th ALTA shared task that ran in 2016. The task was to disambiguate endpoints by determining whether two URLs were referring to the same entity. We present the motivation for the task, the description of the data and the results of the participating teams.
The ALTA shared tasks are programming competitions where all participants attempt to solve the same problem, and the winner is the system with the best results. The 2011 ALTA shared task is the second in the series and it focuses on trying to automatically grade the level of clinical evidence in medical research papers. In this paper we describe the task,… (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)