Finding Related Entities by Retrieving Relations: UIUC at TREC 2009 Entity Track
V. G. Vinod Vydiswaran, Kavita Ganesan, Yuanhua Lv, Jing He, ChengXiang Zhai · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · 2009
Our goal in participating in the TREC 2009 Entity Track was to study whether relation extraction techniques can help in improving accuracy of the entity finding task. Finding related entities is informational in nature and we wanted to explore if inducing structure on the queries helps satisfy this information need. The research outlook we took was to study techniques that retrieve relations between two entities from a large corpus, and from those, find the most relevant entities that participate in the given relation with another given entity. Instead of aiming at retrieving pages about specific entities, we tried to address the problem of directly finding the entities from the text. Our experimental results show that we were able to find many related entities using relation-based extraction, and ranking entities based