Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aït-Mokhtar, S., Chanod, J.-P.: Incremental finite-state parsing. In: Proceedings of the 5th Conference on Applied Natural Language Processing (ANLP 1997), Washington, DC, USA (1997)
Aït-Mokhtar, S., Chanod, J.-P., Roux, C.: Robustness beyond shallowness: incremental deep parsing. Natural Language Engineering 8(2/3), 121–144 (2002)
Brill, E., Lin, J., Banko, M., Dumais, S., Ng, A.: Data-Intensive Question Answering. TREC 10 Notebook, Gaithersburg (2001)
Chu-Carroll, J., Prager, J., Welty, C., Czuba, K., Ferruci, D.: A Multi-Strategy and multi-source Approach to Question Answering. TREC 11 Notebook, Gaithersburg, USA, pp. 124–133 (2002)
Clarke, C.L., Cormack, G.V., Lynam, T.R., Li, C.M., McLearn, G.L.: Web Reinforced Question Answering (MultiText Experiments for Trec 2001). TREC 10 Notebook, Gaithersburg, USA (2001)
Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)
Ferret, O., Grau, B., Hurault-Plantet, M., Illouz, G., Jacquemin, C., Monceaux, L., Robba, I., Vilnat, A.: How NLP Can Improve Question Answering Knowledge Organization 29(3-4), 135–155 (2002)
Hermjakob, U., Echihabi, A., Marcu, D.: Natural Language Based Reformulation Resource and Web Exploitation for Question Answering, TREC 11 Notebook, Gaithersburg, USA (2002)
Magnini, B., Negri, M., Prevete, R., Tanev, H.: Is It the Right Answer? Exploiting Web redundancy for Answer Validation. In: Proceedings of the 40th ACL, pp. 425–432 (2002)
Magnini, B., Negri, M., Prevete, R., Tanev, H.: Mining Knowledge from Repeated Co-occurrences: DIOGENE at TREC-2002. TREC 11 Notebook, Gaithersburg, USA (2002)
Moldovan, D., Harabagiu, S., Girju, R., Morarescu, P., Lacatusu, F., Novischi, A., Badalescu, A., Bolohan, O.: LCC Tools for Question Answering. TREC 11 Notebook, Gaithersburg, USA (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Grau, B. et al. (2005). Answering French Questions in English by Exploiting Results from Several Sources of Information. In: Peters, C., Clough, P., Gonzalo, J., Jones, G.J.F., Kluck, M., Magnini, B. (eds) Multilingual Information Access for Text, Speech and Images. CLEF 2004. Lecture Notes in Computer Science, vol 3491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11519645_46
Download citation
DOI: https://doi.org/10.1007/11519645_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27420-9
Online ISBN: 978-3-540-32051-7
eBook Packages: Computer ScienceComputer Science (R0)