Finding relevant relations in relevant documents

Abstract

This work studies the combination of a document retrieval and a relation extraction system for the purpose of identifying queryrelevant relational facts. On the TRECWeb collection, we assess extracted facts separately for correctness and relevance. Despite some TREC topics not being covered by the relation schema, we find that this approach reveals relevant facts, and in particular those not yet known in the knowledge base DBpedia. The study confirms that mention frequency, document relevance, and entity relevance are useful indicators for fact relevance. Still, the task remains an open research problem.