Leveraging Structural Discourse Information for Event Coreference Resolution in Dutch
Loic De Langhe, Orphee De Clercq, Veronique Hoste
4th Workshop on Computational Approaches to Discourse Regular short Paper
TLDR:
We directly embed easily extractable discourse structure information (subsection, paragraph and text type) in a transformer-based Dutch event coreference resolution model in order to more explicitly provide it with structural information that is known to be important in coreferential relationships.
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Abstract:
We directly embed easily extractable discourse structure information (subsection, paragraph and text type) in a transformer-based Dutch event coreference resolution model in order to more explicitly provide it with structural information that is known to be important in coreferential relationships. Results show that integrating this type of knowledge leads to a significant improvement in CONLL F1 for within-document settings (+ 8.6\textbackslash{}\%) and a minor improvement for cross-document settings (+ 1.1\textbackslash{}\%).