Chinese Metaphorical Relation Extraction
Guihua Chen, Tiantian Wu, MiaoMiao Cheng, Xu Han, Jiefu Gong, Shijin Wang, Wei Song
Abstract
Metaphors are linguistic expressions that convey non-literal meanings, as well as cognitive mappings that establish connections between distinct domains of experience or knowledge. This paper proposes a novel formulation of metaphor identification as a relation extraction problem. We introduce metaphorical relations as links between two spans in text, a target span and a source-related span. We create a dataset for Chinese metaphorical relation extraction, with more than 4,200 sentences annotated with metaphorical relations, corresponding target/source-related spans, and fine-grained span types. Metaphorical relation extraction is a process that detects metaphorical expressions and builds connections between target and source domains. We develop a span-based end-to-end model for metaphorical relation extraction and demonstrate its effectiveness. We expect that metaphorical relation extraction can serve as a bridge between linguistic metaphor identification and conceptual metaphor identification. Our data and code are available at https://github.com/cnunlp/CMRE.
BibTeX
@inproceedings{
chen2023chinese,
title={Chinese Metaphorical Relation Extraction},
author={Guihua Chen and Tiantian Wu and MiaoMiao Cheng and Xu Han and Jiefu Gong and Shijin Wang and Wei Song},
booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing},
year={2023},
url={https://openreview.net/forum?id=RO460OVpev}
}