Contextualized embeddings from ELMo and BERT improve argument classification by 7.4-20.8 points and clustering by 7.8-12.3 points over baselines on multiple datasets.
In Proceed- ings of the 56th Annual Meeting of the Association for Computational Linguistics (V olume 2: Short Pa- pers), volume 2, pages 599–605
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Classification and Clustering of Arguments with Contextualized Word Embeddings
Contextualized embeddings from ELMo and BERT improve argument classification by 7.4-20.8 points and clustering by 7.8-12.3 points over baselines on multiple datasets.