mlsanityData to 7 Oct 2026

HuSpaCy: an industrial-strength Hungarian natural language processing toolkit

arXiv 2201.01956 ↗First posted 6 Jan 2022cs.CL stat.MLcited by 8

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Abstract (arXiv)

Although there are a couple of open-source language processing pipelines available for Hungarian, none of them satisfies the requirements of today's NLP applications. A language processing pipeline should consist of close to state-of-the-art lemmatization, morphosyntactic analysis, entity recognition and word embeddings. Industrial text processing applications have to satisfy non-functional software quality requirements, what is more, frameworks supporting multiple languages are more and more favored. This paper introduces HuSpaCy, an industry-ready Hungarian language processing toolkit. The presented tool provides components for the most important basic linguistic analysis tasks. It is open-source and is available under a permissive license. Our system is built upon spaCy's NLP components resulting in an easily usable, fast yet accurate application. Experiments confirm that HuSpaCy has high accuracy while maintaining resource-efficient prediction capabilities.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 4 of its 39 references that are in the map. First posted on arXiv 6 Jan 2022.

Builds on

4 of 39 references.

References · 4

  1. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  2. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
  3. 2016Neural Architectures for Named Entity Recognitioncited by 548
  4. 2017Recent Trends in Deep Learning Based Natural Language Processingcited by 262

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 1; 2025: 0; 2026: 1.

8 papers.