Selectively Using Relations to Improve Precision in Question Answering

By indexing syntactic relations that can be reliably extracted from corpus text and matching questions with documents at the relation level, it is demonstrated that syntactic analysis enables a question answering system to successfully handle these phenomena, thereby improving precision.

Abstract

Despite the intuition that linguistically sophisticated techniques should be beneficial to question answering, real gains in performance have yet to be demonstrated empirically in a reliable manner. Systems built around sophisticated linguistic analysis generally perform worse than their linguistically-uninformed cousins. We believe that the key to effective application of natural language processing technology is to selectively employ it only when helpful, without abandoning simpler techniques. To this end, we identify two linguistic phenomena that current information extraction driven systems have difficulty with, and demonstrate how syntactic processing can help. By indexing syntactic relations that can be reliably extracted from corpus text and matching questions with documents at the relation level, we demonstrate that syntactic analysis enables a question answering system to successfully handle these phenomena, thereby improving precision.