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Found 2 papers, 2 papers with code
Data-Driven Detection of General Chiasmi Using Lexical and Semantic Features
In contrast, we propose an approach targeting the more general and challenging case A B B’ A’, where the words A, A’ and B, B’ constituting the chiasmus do not need to be identical but just related in meaning.
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German
We train this method in a zero-shot pseudo-supervised manner by generating artificial metaphor examples and show that our approach can be used to generate a metaphor dataset with low annotation cost.
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