YAGO-QA: Answering Questions by Structured Knowledge Queries

Abstract

We present a natural-language question-answering system that gives access to the accumulated knowledge of one of the largest community projects on the Web â€" Wikipedia â€" via an automatically acquired structured knowledge base. Key to building such a system is to establish mappings from natural language expressions to semantic representations. We propose to acquire these mappings by data-driven methods â€" corpus harvesting and paraphrasing â€" and present a preliminary empirical study that demonstrates the viability of our method.