Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing
René Knaebel, Manfred Stede · 2020
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.