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State-of-the-art, lightweight NLP tools for Turkish language. Developed by VNGRS.
| Date | Stars |
|---|---|
| 2026-07-24 | 289 |
| 2026-07-25 | 289 |
| 2026-07-28 | 289 |
| 2026-07-30 | 289 |
| 2026-08-06 | 289 |
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<img src="https://github.com/vngrs-ai/vnlp/blob/main/img/logo.png?raw=true" width="256"> ## VNLP: Turkish NLP Tools State-of-the-art, lightweight NLP tools for Turkish language. Developed by VNGRS. https://vngrs.com/ [](https://badge.fury.io/py/vngrs-nlp) [](https://pypi.org/project/vngrs-nlp/) [](https://vnlp.readthedocs.io/) [](https://github.com/vngrs-ai/vnlp/blob/main/LICENSE) [](https://github.com/vngrs-ai/vnlp/actions/workflows/test.yml) ### Functionality: - Sentence Splitter - Normalizer - Spelling/Typo correction - Convert numbers to word form - Deasciification - Stopword Remover: - Static - Dynamic - Stemmer: Morphological Analyzer & Disambiguator - Named Entity Recognizer (NER) - Dependency Parser - Part of Speech (PoS) Tagger - Sentiment Analyzer - Turkish Word Embeddings - FastText - Word2Vec - SentencePiece Unigram Tokenizer - News Summarization - News Paraphrasing - Summarization and Paraphrasing models are available in the demo. Contact us at [email protected] for API. ### Demo: - Try the [Demo](https://demo.vnlp.io). ### Installation ``` pip install vngrs-nlp ``` ### Documentation: - See the [Documentation](https://vnlp.readthedocs.io) for the details about usage, classes, functions, datasets and evaluation metrics. ### Metrics: <img src="https://github.com/vngrs-ai/vnlp/blob/main/img/metrics.png?raw=true" width="600"> <img src="https://github.com/vngrs-ai/vnlp/blob/main/img/sum_metrics.png?raw=true" width="124"> ### Usage Example: **Dependency Parser** ``` from vnlp import DependencyParser dep_parser = DependencyParser() dep_parser.predict("Oğuz'un kırmızı bir Astra'sı vardı.") [("Oğuz'un", 'PROPN'), ('kırmızı', 'ADJ'), ('bir', 'DET'), ("Astra'sı", 'PROPN'), ('vardı', 'VERB'), ('.', 'PUNCT')] # Spacy's submodule Displacy can be used to visualize DependencyParser result. import spacy from vnlp import DependencyParser dependency_parser = DependencyParser() result = dependency_parser.predict("Oğuz'un kırmızı bir Astra'sı vardı.", displacy_format = True) spacy.displacy.render(result, style="dep", manual = True) ``` <img src="https://raw.githubusercontent.com/vngrs-ai/vnlp/main/img/dp_vis_sample.png" width="512"> ## Citation ```bibtex @article{turker2024vnlp, title={VNLP: Turkish NLP Package}, author={Turker, Meliksah and Ari, Erdi and Han, Aydin}, journal={arXiv preprint arXiv:2403.01309}, year={2024} } ```
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e2181af0091598c6, topic:nlp, topic:named-entity-recognition, topic:sentiment-analysis