Chinese Metaphorical Relation Extraction
EMNLP 2023(2023)
摘要
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.
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