Target Word Masking for Location Metonymy Resolution
Haonan Li, Maria Vasardani, Martin Tomko, Timothy J. Baldwin · 2020
Existing metonymy resolution approaches rely on features extracted from external resources like dictionaries and hand-crafted lexical resources.In this paper, we propose an end-to-end word-level classification approach based only on BERT, without dependencies on taggers, parsers, curated dictionaries of place names, or other external resources.We show that our approach achieves the state-of-the-art on 5 datasets, surpassing conventional BERT models and benchmarks by a large margin.We also show that our approach generalises well to unseen data.