YAGO-QA: Answering Questions by Structured Knowledge Queries

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 - Wikipedia - 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 - corpus harvesting and paraphrasing and present a preliminary empirical study that demonstrates the viability of our method.