Pocket Knowledge Base Population
Travis Wolfe, Mark H. Dredze, Benjamin Van Durme · 2017
Existing Knowledge Base Population methods extract relations from a closed relational schema with limited coverage, leading to sparse KBs.We propose Pocket Knowledge Base Population (PKBP), the task of dynamically constructing a KB of entities related to a query and finding the best characterization of relationships between entities.We describe novel Open Information Extraction methods which leverage the PKB to find informative trigger words.We evaluate using existing KBP shared-task data as well as new annotations collected for this work.Our methods produce high quality KBs from just text with many more entities and relationships than existing KBP systems.