An Analysis of Sentential Neighbors in Implicit Discourse Relation Prediction
Judge, Evi, Suchocki, Reece, Syed, Konner
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
May-16-2024
- Country:
- North America > United States
- Minnesota > Hennepin County
- Minneapolis (0.04)
- Colorado > Boulder County
- Boulder (0.04)
- Minnesota > Hennepin County
- North America > United States
- Genre:
- Research Report
- New Finding (0.67)
- Experimental Study (0.47)
- Research Report
- Technology: