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The TREC Question Answering Track

Published

Author(s)

Ellen M. Voorhees

Abstract

The Text REtrieval Conference (TREC) question answering track is an effort to bring the benefits of large-scale evaluation to bear on a question answering (QA) task. The track has run twice so far, first in TREC-8 and again in TREC-9. In each case the goal was to retrieve small snippets of text that contain the actual answer to a question rather than the document lists traditionally returned by text retrieval systems. The best performing systems were able to answer about 70% of the questions in TREC-8 and about 65% of the questions in TREC-9. While the 65% score is a slightly worse result than the TREC-8 scores in absolute terms, it represents a very significant improvement in question answering systems. The TREC-9 task was considerably harder than the TREC-8 task because TREC-9 used actual users' questions while TREC-8 used questions constructed for the track. Future tracks will continue to challenge the QA community with more difficult, and more realistic, question answering tasks.
Citation
Natural Language Engineering
Volume
7
Issue
No. 4

Keywords

natural language processing, question answering, TREC

Citation

Voorhees, E. (2001), The TREC Question Answering Track, Natural Language Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=151518 (Accessed April 19, 2024)
Created October 29, 2001, Updated February 17, 2017