arXiv cs.CL· Isaac Rudnick, Nipun Das, Foaad Khosmood·· 11 小时前AI 评分20
立法议案讨论的话语分析：从听证会转录文本解析修辞结构
Discourse Analysis of Legislative Bill Discussions
AI 导读
研究提出一套端到端流水线，从立法委员会听证会转录文本中解析修辞结构，并给出修辞结构语法，发现数据集中 55.21% 的加州州级议案讨论可按该语法解析。在 100 场听证会、2000 余条标注话语上评测两个话语段落分类器，基于逻辑回归、结合语法输出掩码与话语标签平滑的分类器优于更复杂模型，F1 为 52.8%。
正文 · 原文
Abstract:Legislative hearings are distinct communication events with their own human recognizable structure and logic, yet they have been analyzed as distinct phenomena beyond their transcripts. Understanding legislative hearings at a deeper level is a major step in analyzing the work and power relationships within democratic bodies. In this work, we present a novel end-to-end pipeline for parsing rhetorical structures from legislative committee hearings with the goal of improving legislative discourse analysis and democratic accountability. We also propose a rhetorical structure grammar and find that 55.21% of California state bill discussions in our dataset can be parsed with this grammar. We evaluate our pipeline with two utterance section classifiers on a random subset of over 2,000 annotated utterances corresponding to 100 hearings. We find that a logistic regression-based classifier with grammar-based output masking and utterance tag smoothing outperforms more complex models, achieving an F1 score of 52.8% against our ground truth discourse section labels.
| Comments: | 10 pages, 4 figures |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2611.05381 [cs.CL] |
| (or arXiv:2611.05381v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2611.05381 arXiv-issued DOI via DataCite |
Submission history
From: Isaac Rudnick [view email]
[v1]
Thu, 30 Jul 2026 00:13:23 UTC (1,193 KB)
来源：arXiv cs.CL · arxiv.org