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arXiv · 2406.18256

Llamipa: An Incremental Discourse Parser

Kate Thompson·Akshay Chaturvedi·Julie Hunter·Nicholas Asher
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Abstract

This paper provides the first discourse parsing experiments with a large language model(LLM) finetuned on corpora annotated in the style of SDRT (Segmented Discourse Representation Theory Asher, 1993; Asher and Lascarides, 2003). The result is a discourse parser, Llamipa (Llama Incremental Parser), that leverages discourse context, leading to substantial performance gains over approaches that use encoder-only models to provide local, context-sensitive representations of discourse units. Furthermore, it can process discourse data incrementally, which is essential for the eventual use of discourse information in downstream tasks.

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Kate Thompson, Akshay Chaturvedi, Julie Hunter, Nicholas Asher. 2024-06-26. Llamipa: An Incremental Discourse Parser. https://arxiv.org/abs/2406.18256

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