VNLP: Turkish NLP Package
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Abstract (arXiv)
In this work, we present VNLP: the first dedicated, complete, open-source, well-documented, lightweight, production-ready, state-of-the-art Natural Language Processing (NLP) package for the Turkish language. It contains a wide variety of tools, ranging from the simplest tasks, such as sentence splitting and text normalization, to the more advanced ones, such as text and token classification models. Its token classification models are based on "Context Model", a novel architecture that is both an encoder and an auto-regressive model. NLP tasks solved by VNLP models include but are not limited to Sentiment Analysis, Named Entity Recognition, Morphological Analysis & Disambiguation and Part-of-Speech Tagging. Moreover, it comes with pre-trained word embeddings and corresponding SentencePiece Unigram tokenizers. VNLP has an open-source GitHub repository, ReadtheDocs documentation, PyPi package for convenient installation, Python and command-line API and a demo page to test all the functionality. Consequently, our main contribution is a complete, compact, easy-to-install and easy-to-use NLP package for Turkish.
Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 16 of its 47 references that are in the map. First posted on arXiv 2 Mar 2024.
Builds on
16 of 47 references.
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4 more
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Citing papers per year: 2025: 1.
1 paper.
- 2025TurkEmbed: Turkish Embedding Model on NLI & STS Taskscited by 0
- 2025TurkEmbed: Turkish Embedding Model on NLI & STS Tasks11 Nov 2025