Abstract
Metonymy is a figure of speech in which an entity is referred to by another related entity. The existing datasets of metonymy are either too small in size or lack sufficient coverage. We propose a new, labelled, high-quality corpus of location metonymy called WiMCor, which is large in size and has high coverage. The corpus is harvested semi-automatically from English Wikipedia. We use different labels of varying granularity to annotate the corpus. The corpus can directly be used for training and evaluating automatic metonymy resolution systems. We construct benchmarks for metonymy resolution, and evaluate baseline methods using the new corpus.- Anthology ID:
- 2020.lrec-1.697
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 5678–5687
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.697
- DOI:
- Cite (ACL):
- Kevin Alex Mathews and Michael Strube. 2020. A Large Harvested Corpus of Location Metonymy. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5678–5687, Marseille, France. European Language Resources Association.
- Cite (Informal):
- A Large Harvested Corpus of Location Metonymy (Alex Mathews & Strube, LREC 2020)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2020.lrec-1.697.pdf