Improving Hypernymy Detection with an Integrated Path-based and Distributional Method
Vered Shwartz, Yoav Goldberg, Ido Dagan · 2016
Detecting hypernymy relations is a key task in NLP, which is addressed in the literature using two complementary approaches.Distributional methods, whose supervised variants are the current best performers, and path-based methods, which received less research attention.We suggest an improved path-based algorithm, in which the dependency paths are encoded using a recurrent neural network, that achieves results comparable to distributional methods.We then extend the approach to integrate both pathbased and distributional signals, significantly improving upon the state-of-the-art on this task.