LIMSI-CNRS@CLEF 2015: Tree Edit Beam Search for Multiple Choice Question Answering

LIMSI-CNRS@CLEF 2014: Invalidating Answers for Multiple Choice Question Answering

This paper describes our participation to the Entrance Exams Task of CLEF 2014’s Question Answering Track. The goal is to answer multiple-choice questions on short texts. Our system first retrieves passages relevant to the question, through lexical expansion involving a structured use of the Simple English Wiktionary and WordNet. Then it extracts predicate-argument structures (PAS) from each an...

LIMSI participation in the QAst 2009 track

We present in this paper the three LIMSI question-answering systems on speech transcripts which participated to the QAst 2009 evaluation. These systems are based on a complete and multi-level analysis of both queries and documents. These systems use an automatically generated research descriptor. A score based on those descriptors is used to select documents and snippets. Three different method...

QALC--The Question-Answering System of LIMSI-CNRS

The DI@UE's Participation in QA4MRE: from QA to Multiple Choice Challenge

This QA4MRE edition brought two challenges to the DI@UE team: the absence of Portuguese as a working language and the different nature of the task when compared with previous participation in QA@CLEF. We addressed this multiple choice answering problem by assessing answer candidates in a text surface based manner, without a deep linguistic processing. This system employs a Lucene based search e...

QALC - the Question-Answering program of the Language and Cognition group at LIMSI-CNRS

In this report we describe the QALC system (the Question-Answering program of the Language and Cognition group at LIMSI-CNRS) which has been involved in the QA-track evaluation at TREC8. The purpose of the Question-Answering track is to nd the answers to a set of 200 questions. The answers are text sequences extracted from the volumes 4 and 5 of the TREC collection. All the questions have at le...