Paper: Learning Surface Text Patterns For A Question Answering System

ACL ID P02-1006
Title Learning Surface Text Patterns For A Question Answering System
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2002
Authors

In this paper we explore the power of surface text patterns for open - domain question answering systems. In order to obtain an optimal set of patterns, we have developed a method for learning such patterns automatically. A tagged corpus is built from the In ternet in a bootstrapping process by providing a few hand -crafted examples of each question type to Altavista. Patterns are then automatically extracted from the returned documents and standardized. We calculate the precision of each pattern, and the avera ge precision for each question type. These patterns are then applied to find answers to new questions. Using the TREC -10 question set, we report results for two cases: answers determined from the TREC - 10 corpus and from the web.