Abstract
In this paper, we describe our Question Answering (QA) system called QUANTUM. The goal of QUANTUM is to find the answer to a natural language question in a large document collection. QUANTUM relies on computational linguistics as well as information retrieval techniques. The system analyzes questions using shallow parsing techniques and regular expressions, then selects the appropriate extraction function. This extraction function is then applied to one-paragraph-long passages retrieved by the Okapi information retrieval system. The extraction process involves the Alembic named entity tagger and the WordNet semantic network to identify and score candidate answers. We designed QUANTUM according to the TREC-X QA track requirements; therefore, we use the TREC-X data set and tools to evaluate the overall system and each of its components.
Work performed while at the Université de Montréal.
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
E. M. Voorhees. Overview of the TREC 2001 Question Answering Track. In Notebook Proceedings of The Tenth Text REtrieval Conference (TREC-X), pages 157–165, Gaithersburg, Maryland, 2001.
L. Plamondon, L. Kosseim, and G. Lapalme. The QUANTUM Question Answering System. In Notebook Proceedings of The Tenth Text REtrieval Conference (TRECX), pages 571–577, Gaithersburg, Maryland, 2001.
S. Harabagiu, D. Moldovan, M. Pasca, R. Mihalcea, M. Surdeanu, R. Bunescu, R. Girju, V. Rus, and P. Morarescu. FALCON: Boosting Knowledge for Answer Engines. In Proceedings of The Ninth Text REtrieval Conference (TREC-9), pages 479–488, 2000.
O. Ferret, B. Grau, M. Hurault-Plantet, G. Illouz, C. Jacquemin, N. Masson, and P. Lecuyer. QALC-The Question-Answering System of LIMSI-CNRS. In Proceedings of The Ninth Text REtrieval Conference (TREC-9), pages 325–334, 2000.
S. E. Robertson and S. Walker. Okapi/Keenbow at TREC-8. In Proceedings of The Eighth Text REtrieval Conference (TREC-8), pages 151–162, Gaithersburg, Maryland, 1998.
J. Aberdeen, J. Burger, D. Day, L. Hirschman, P. Robinson, and M. Vilain. MITRE: Description of the Alembic System as used for MUC-6. In Proceedings of the Sixth Message Understanding Conference (MUC-6), San Francisco, 1995. Morgan Kaufman Publishers.
C. L. A. Clarke, G. V. Cormack, T. R. Lynam, C. M. Li, and G. L. McLearn. Web Reinforced Question Answering (MultiText Experiments for TREC 2001). In Notebook Proceedings of The Tenth Text REtrieval Conference (TREC-X), pages 620–626, Gaithersburg, Maryland, 2001.
E. Hovy, U. Hermjakob, and C.-Y. Lin. The Use of External Knowledge in Factoid QA. In Notebook Proceedings of The Tenth Text REtrieval Conference (TREC-X), pages 166–174, Gaithersburg, Maryland, 2001.
E. Brill, J. Lin, M. Banko, S. Dumais, and A. Ng. Data-Intensive Question Answering. In Notebook Proceedings of The Tenth Text REtrieval Conference (TREC-X), pages 183–189, Gaithersburg, Maryland, 2001.
NIST. Notebook Proceedings of The Tenth Text REtrieval Conference (TREC-X), Gaithersburg, Maryland, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Plamondon, L., Kosseim, L. (2002). QUANTUM: A Function-Based Question Answering System. In: Cohen, R., Spencer, B. (eds) Advances in Artificial Intelligence. Canadian AI 2002. Lecture Notes in Computer Science(), vol 2338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47922-8_23
Download citation
DOI: https://doi.org/10.1007/3-540-47922-8_23
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43724-6
Online ISBN: 978-3-540-47922-2
eBook Packages: Springer Book Archive