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Managing Growth in a National Corpus: The Hungarian National Corpus 3.0 (MNSZ3)

The third generation of the Hungarian National Corpus (MNSZ3) aims to provide a large-scale, curated, and well-described corpus resource needed for the sustainable digital presence of Hungarian. Building on the domain structure and proportions of MNSZ2 (v2.0.5; 1.04 billion running words), the project targets a substantial increase in scale while also strengthening the coverage and metadata description of Hungarian language use outside Hungary. MNSZ3 retains the six traditional domains of the earlier corpus—press, fiction, scientific, official, personal, and transcribed spoken language—and is planned to reach approximately 10 billion tokens. This paper presents the motivation and design principles of the project, outlines the practical decisions and procedures used in data collection and cleaning, and discusses the annotation strategy developed for large-scale processing. In planning the linguistic analysis, we build on the complementary strengths of HuSpaCy and e-magyar: HuSpaCy provides the unified and efficient UD-oriented processing backbone, while e-magyar (emMorph) is preserved as an explicit additional layer for morphology and lemmatisation.