Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines

• URL: http://arxiv.org/abs/2308.12635v1
• Date: Thu, 24 Aug 2023 08:19:51 GMT
• Title: Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines
• Authors: Gy\"orgy Orosz and Gerg\H{o} Szab\'o and P\'eter Berkecz and Zsolt Sz\'ant\'o and Rich\'ard Farkas
• Abstract summary: This paper presents a set of industrial-grade text processing models for Hungarian. Models have been implemented in the spaCy framework, extending the HuSpaCy toolkit. All experiments are reproducible and the pipelines are freely available under a permissive license.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: This paper presents a set of industrial-grade text processing models for Hungarian that achieve near state-of-the-art performance while balancing resource efficiency and accuracy. Models have been implemented in the spaCy framework, extending the HuSpaCy toolkit with several improvements to its architecture. Compared to existing NLP tools for Hungarian, all of our pipelines feature all basic text processing steps including tokenization, sentence-boundary detection, part-of-speech tagging, morphological feature tagging, lemmatization, dependency parsing and named entity recognition with high accuracy and throughput. We thoroughly evaluated the proposed enhancements, compared the pipelines with state-of-the-art tools and demonstrated the competitive performance of the new models in all text preprocessing steps. All experiments are reproducible and the pipelines are freely available under a permissive license.

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