This article presents the Polish contribution to the PressMint project, a CLARIN initiative aimed at creating a pan-European, multilingual corpus of historical newspapers. The Polish dataset consists of three subcorpora spanning 110 years (1830–1939). The first two components are drawn from the Microcorpus of Nineteenth-Century Polish (its short press texts and journalistic texts subcorpora), each containing 200 samples of brief news items and journalistic articles from diverse periodicals. The third component, the InterWar Corpus, covers the period 1918–1939 and comprises approximately 6.5 million words from complete newspaper issues, representing the territory of the interwar Republic of Poland. The authors argue for the scholarly value of historical press, highlighting its precise chronological dating as a key advantage for diachronic research despite challenges such as heterogeneous content and anonymous authorship. The conversion pipeline maps source metadata to a standardized TEI format and enriches texts with linguistic annotation using the Hydra NLP tool, providing lemmatization, part-of-speech tagging (mapped to Universal Dependencies), dependency parsing, and named entity recognition. The resulting openly accessible dataset enables cross-linguistic comparison and distant reading of historical press materials on a European scale.

We present LocalGovPL, a large-scale, speaker-annotated corpus of Polish local government meeting transcripts processed using an automatic two-stage LLM pipeline. The corpus consists of 31,900 sessions from 749 councils recorded between 2018–2025 (approximately 391M words). It is released in TEI P5 format with explicit links between utterances and registered participants. We collect transcripts from official local government portals using a dedicated crawler, normalize the text, and apply: (1) LLM-assisted extraction of person names and administrative roles; and (2) attribution of utterances to identified speakers using discourse cues. To evaluate attribution quality, we manually annotate 30 sessions and evaluate five LLM configurations using three evaluation protocols with speaker-aware word error rate (sWER). The strongest system, Gemini-2.5-pro, achieves 3.9% sWER for abstract speaker identification, 4.6% for known participants, and 5.9% for end-to-end processing with relaxed name matching. LocalGovPL enables large-scale analysis of local deliberative discourse and supports research on dialogue modeling, summarization, and political text analysis.

This paper presents an extension of the ISO 24617-8 ontology for discourse relations through the integration of corpus-based examples and the development of a dedicated Ontology Viewer. The goal is to bridge the gap between formal ontological representations and practical corpus-based linguistic analysis, making discourse annotation frameworks more accessible to researchers. The proposed approach introduces a method for populating the ISO ontology with instances derived from three corpora (in Polish and English) compliant with the ISO 24617-8 standard. These instances formally connect discourse relations, argument roles, and explicit connectives within a unified semantic model. The Ontology Viewer enables intuitive browsing, filtering, and full-text searching of examples by language, relation type, and connective, offering both a relation-oriented and connective-oriented perspective. The experiment demonstrates the feasibility and effectiveness of this corpus-driven instantiation method and its visualization. The system provides a foundation for future integration of multilingual discourse corpora and contributes to the development of interoperable language resources for the Semantic Web and Natural Language Processing applications.