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- W3100550141 abstract "This paper studies a novel model that simplifies the disambiguation of connectives for explicit discourse relations. We use a neural approach that integrates contextualized word embeddings and predicts whether a connective candidate is part of a discourse relation or not. We study the influence of those context-specific embeddings. Further, we show the benefit of training the tasks of connective disambiguation and sense classification together at the same time. The success of our approach is supported by state-of-the-art results." @default.
- W3100550141 created "2020-11-23" @default.
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- W3100550141 date "2020-01-01" @default.
- W3100550141 modified "2023-10-16" @default.
- W3100550141 title "Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing" @default.
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- W3100550141 doi "https://doi.org/10.18653/v1/2020.codi-1.7" @default.
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