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

arXiv cs.CL / 3/30/2026

💬 OpinionIdeas & Deep AnalysisModels & Research

Key Points

  • The paper introduces CitiLink-Minutes, a multilayer annotated dataset of 120 European Portuguese municipal meeting minutes aimed at improving NLP/IR research on local governance records.
  • The dataset includes over one million tokens and features comprehensive, structured annotations across three dimensions: metadata, subjects of discussion, and voting outcomes (38,000+ annotations).
  • Personal identifiers are de-identified, and each minute is manually annotated by two trained annotators with additional curation by an experienced linguist.
  • CitiLink-Minutes is released under FAIR principles and comes with baseline results for tasks such as metadata extraction, topic classification, and vote labeling.
  • By providing linked, official written minutes with multilayer annotation, the dataset is positioned to support downstream computational models and more transparent access to municipal decision-making.

Abstract

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.