%0 Generic %1 li2020target %A Li, Haonan %A Vasardani, Maria %A Tomko, Martin %A Baldwin, Timothy %D 2020 %K BERT m metonymy sequence-tagging %T Target Word Masking for Location Metonymy Resolution %U http://arxiv.org/abs/2010.16097 %X 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.

@misc{li2020target, abstract = {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.}, added-at = {2022-01-24T11:21:39.000+0100}, author = {Li, Haonan and Vasardani, Maria and Tomko, Martin and Baldwin, Timothy}, biburl = {https://www.bibsonomy.org/bibtex/2477331d184f436c8d673d6e3d49e03df/mschwab}, description = {2010.16097.pdf}, interhash = {87830e7b8ddefeeda3171808928834a5}, intrahash = {477331d184f436c8d673d6e3d49e03df}, keywords = {BERT m metonymy sequence-tagging}, note = {cite arxiv:2010.16097Comment: 12 pages}, timestamp = {2022-01-24T11:21:39.000+0100}, title = {Target Word Masking for Location Metonymy Resolution}, url = {http://arxiv.org/abs/2010.16097}, year = 2020 }