Hierarchical Entity Typing via Multi-level Learning to Rank
2020-04-05ACL 2020Code Available1· sign in to hype
Tongfei Chen, Yunmo Chen, Benjamin Van Durme
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/ctongfei/hierarchical-typingOfficialpytorch★ 12
Abstract
We propose a novel method for hierarchical entity classification that embraces ontological structure at both training and during prediction. At training, our novel multi-level learning-to-rank loss compares positive types against negative siblings according to the type tree. During prediction, we define a coarse-to-fine decoder that restricts viable candidates at each level of the ontology based on already predicted parent type(s). We achieve state-of-the-art across multiple datasets, particularly with respect to strict accuracy.