Finding patterns in a knowledge base using keywords to compose table answers

Finding Patterns in a Knowledge Base using Keywords to Compose Table Answers

We aim to provide table answers to keyword queries using a knowledge base. For queries referring to multiple entities, like “Washington cities population” and “Mel Gibson movies”, it is better to represent each relevant answer as a table which aggregates a set of entities or joins of entities within the same table scheme or pattern. In this paper, we study how to find highly relevant patterns i...

Finding Answers Using Resources in the Internet

In this paper we describe our experiments in finding answers from documents based on statistical and linguistic knowledge. We collected the candidate answers from sources available on the internet, and then we used them to validate the answers found in the documents. The candidate answers from the documents were found using a statistical technique and linguistic knowledge such as named entity t...

Web-Scale Web Table to Knowledge Base Matching

Millions of relational HTML tables are found on the World Wide Web. In contrast to unstructured text, relational web tables provide a compact representation of entities described by attributes. The data within these tables covers a broad topical range. Web table data is used for question answering, augmentation of search results, and knowledge base completion. Until a few years ago, only search...

Finding Answers to Definition Questions

Current researches on Question Answering concern more complex questions than factoid ones. Since definition questions are investigated by many researches, how to acquire accurate answers still becomes a core problem for definition QA. Although some systems use web knowledge bases to improve answer acquisition, we propose an approach that leverage them in an effective way. After summarizing defi...

Finding Answers to Complex Questions