Paper: Examining The Role Of Statistical And Linguistic Knowledge Sources In A General-Knowledge Question-Answering System

ACL ID A00-1025
Title Examining The Role Of Statistical And Linguistic Knowledge Sources In A General-Knowledge Question-Answering System
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000
Authors

We describe and evaluate an implemented system for general-knowledge question answering. The sys- tem combines techniques for standard ad-hoc infor- mation retrieval (IR), query-dependent text summa- rization, and shallow syntactic and semantic sen- tence analysis. In a series of experiments we examine the role of each statistical and linguistic knowledge source in the question-answering system. In con- trast to previous results, we find first that statisti- cal knowledge of word co-occurrences as computed by IR vector space methods can be used to quickly and accurately locate the relevant documents for each question. The use of query-dependent text summarization techniques, however, provides only small increases in performance and severely limits recall levels when inaccurate. Nevertheles...