Extracting Definitions and Hypernyms with a Two-Phase Framework

Yifang Sun, Shifeng Liu, Yufei Wang, Wei Wang

Abstract: Extracting definition sentences and hypernyms is the key step in knowledge graph construction as well as many other NLP applications. In this paper, we propose a novel supervised two-phase machine learning framework to solve both tasks simultaneously. Firstly, a joint neural network is trained to predict both definition sentences and hypernyms. Then a refinement model is utilized to further improve the performance of hypernym extraction. Experiment result shows the effectiveness of our proposed framework on a well-known benchmark.