Vancouver Welcomes You! Minimalist Location Metonymy Resolution

Milan Gritta, Mohammad Taher Pilehvar, Nut Limsopatham, Nigel Collier


Abstract
Named entities are frequently used in a metonymic manner. They serve as references to related entities such as people and organisations. Accurate identification and interpretation of metonymy can be directly beneficial to various NLP applications, such as Named Entity Recognition and Geographical Parsing. Until now, metonymy resolution (MR) methods mainly relied on parsers, taggers, dictionaries, external word lists and other handcrafted lexical resources. We show how a minimalist neural approach combined with a novel predicate window method can achieve competitive results on the SemEval 2007 task on Metonymy Resolution. Additionally, we contribute with a new Wikipedia-based MR dataset called RelocaR, which is tailored towards locations as well as improving previous deficiencies in annotation guidelines.
Anthology ID:
P17-1115
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Editors:
Regina Barzilay, Min-Yen Kan
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1248–1259
Language:
URL:
https://aclanthology.org/P17-1115
DOI:
10.18653/v1/P17-1115
Bibkey:
Cite (ACL):
Milan Gritta, Mohammad Taher Pilehvar, Nut Limsopatham, and Nigel Collier. 2017. Vancouver Welcomes You! Minimalist Location Metonymy Resolution. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1248–1259, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Vancouver Welcomes You! Minimalist Location Metonymy Resolution (Gritta et al., ACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/P17-1115.pdf
Dataset:
 P17-1115.Datasets.zip
Video:
 https://aclanthology.org/P17-1115.mp4
Code
 milangritta/Minimalist-Location-Metonymy-Resolution