Multi-token Mask-filling and Implicit Discourse Relations
Meinan Liu, Yunfang Dong, Xixian Liao, Bonnie Webber
Abstract
Previous work has shown that simple mask-filling can provide useful information about the discourse informativeness of syntactic structures. Dong et al. (2024) first adopted this approach to investigating preposing constructions. The problem with single token mask fillers was that they were, by and large, ambiguous. We address the issue by adapting the approach of Kalinsky et al. (2023) to support the prediction of multi-token connectives in masked positions. Our first experiment demonstrates that this multi-token mask-filling approach substantially outperforms the previously considered single-token approach in recognizing implicit discourse relations. Our second experiment corroborates previous findings, providing additional empirical support for the role of preposed syntactic constituents in signaling discourse coherence. Overall, our study extends existing mask-filling methods to a new discourse-level task and reinforces the linguistic hypothesis concerning the discourse informativeness of preposed structures.
BibTeX
@inproceedings{emnlp2025_multitokenmaskfi,
title = {Multi-token Mask-filling and Implicit Discourse Relations},
author = {Meinan Liu and Yunfang Dong and Xixian Liao and Bonnie Webber},
booktitle = {EMNLP 2025},
year = {2025}
}