Pattern learning for relation extraction with a hierarchical topic model
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2, page 54--59. Stroudsburg, PA, USA, Association for Computational Linguistics, (2012)Abstract
We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant supervision using relations from the knowledge base FreeBase, but do not require any manual heuristic nor manual seed list selections. Results show that the learned patterns can be used to extract new relations with good precision.
Description
Pattern learning for relation extraction with a hierarchical topic model
