An Analysis of Sentential Neighbors in Implicit Discourse Relation Prediction
Computation and Language
2024-05-20 v2
Abstract
Discourse relation classification is an especially difficult task without explicit context markers (Prasad et al., 2008). Current approaches to implicit relation prediction solely rely on two neighboring sentences being targeted, ignoring the broader context of their surrounding environments (Atwell et al., 2021). In this research, we propose three new methods in which to incorporate context in the task of sentence relation prediction: (1) Direct Neighbors (DNs), (2) Expanded Window Neighbors (EWNs), and (3) Part-Smart Random Neighbors (PSRNs). Our findings indicate that the inclusion of context beyond one discourse unit is harmful in the task of discourse relation classification.
Cite
@article{arxiv.2405.09735,
title = {An Analysis of Sentential Neighbors in Implicit Discourse Relation Prediction},
author = {Evi Judge and Reece Suchocki and Konner Syed},
journal= {arXiv preprint arXiv:2405.09735},
year = {2024}
}