arXiv:2602.12137cs.CL2026-02被引 2

首个葡萄牙语市政会议记录多层标注数据集,助力本地治理研究

CitiLink-Minutes: A Multilayer Annotated Dataset of Municipal Meeting Minutes

  • 构建120份市政会议纪要的多层标注体系,涵盖元数据、议题与投票结果
  • 含超百万词元,38000+人工标注,个人身份信息已脱敏
  • 适合研究政务公开、信息检索与自然语言处理的学者使用

城市议会是地方治理的关键,其会议纪要是决策过程的正式记录,直接影响市民生活。然而,由于缺乏标注数据集,这些重要文本在信息检索(IR)和自然语言处理(NLP)领域长期未受重视。为此,我们推出CitiLink-Minutes,一个包含120份欧洲葡萄牙语市政会议纪要的多层标注数据集,来自六个市镇。该数据集不同于以往对议会或视频记录的标注,首次实现了官方书面纪要的结构化链接与多维度标注。数据总量超过一百万词元,所有个人身份信息均已去标识化。每份纪要由两名训练有素的标注员人工标注,并经资深语言学家审核,涵盖三个互补维度:(1) 元数据,(2) 讨论主题,(3) 投票结果,总计超过38,000项独立标注。数据集遵循开放科学原则发布,并提供元数据提取、主题分类与投票标注的基线结果,展现其在下游NLP与IR任务中的潜力,推动市政决策透明化与可计算研究。

原文摘要 · Abstract (English)

City councils play a crucial role in local governance, directly influencing citizens' daily lives through decisions made during municipal meetings. These deliberations are formally documented in meeting minutes, which serve as official records of discussions, decisions, and voting outcomes. Despite their importance, municipal meeting records have received little attention in Information Retrieval (IR) and Natural Language Processing (NLP), largely due to the lack of annotated datasets, which ultimately limit the development of computational models. To address this gap, we introduce CitiLink-Minutes, a multilayer dataset of 120 European Portuguese municipal meeting minutes from six municipalities. Unlike prior annotated datasets of parliamentary or video records, CitiLink-Minutes provides multilayer annotations and structured linkage of official written minutes. The dataset contains over one million tokens, with all personal identifiers de-identified. Each minute was manually annotated by two trained annotators and curated by an experienced linguist across three complementary dimensions: (1) metadata, (2) subjects of discussion, and (3) voting outcomes, totaling over 38,000 individual annotations. Released under FAIR principles and accompanied by baseline results on metadata extraction, topic classification, and vote labeling, CitiLink-Minutes demonstrates its potential for downstream NLP and IR tasks, while promoting transparent access to municipal decisions.

政务公开多层标注自然语言处理数据集

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