Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysis (2023.acl-long)
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| Challenge: | Existing approaches to semantic change analysis are limited in their interpretation power and lack of explanatory power. |
| Approach: | They propose to use specialised Flan-T5 language models to generate a definition for each usage and a specialised word sense model to generate the most prototypical definition. |
| Outcome: | The proposed representations outperform token or usage sentence embeddings in word-in-context semantic similarity judgements and are a promising type of lexical representation for NLP. |
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