Hazm tokenizer. . Hazm is built on top of the NLTK library ...
Hazm tokenizer. . Hazm is built on top of the NLTK library and is specifically optimized for the Persian language. Furthermore, it showed that using word bound morphemes and Farsi Verb tokenizer can slightly improve the results. It provides tools for text normalization, sentence and word tokenization, stemming, lemmatization, part-of-speech tagging, syntactic dependency parsing, and more. You can use Hazm to normalize text, tokenize sentences and words, lemmatize words, assign part-of-speech tags, identify dependency relations, create word and sentence embeddings, or read popular Persian corpora. It is fully compatible with Python 3. 12+. Hazm has shown the best performance on Persian Dependency[16] among all of the available tokenizers. This blog will guide you step-by-step through the features, installation, usage, and more of Hazm in a clear and user-friendly manner. It offers various features for analyzing, processing, and understanding Persian text. Jan 24, 2025 · Hazm is a natural language processing (NLP) library for Persian text, offering various tools for text preprocessing, tokenization, part-of-speech tagging, and more. It offers various features for analyzing, processing, and understanding Persian text. Dec 20, 2025 · You can use Hazm to normalize text, tokenize sentences and words, lemmatize words, assign part-of-speech tags, identify dependency relations, create word and sentence embeddings, or read popular Persian corpora. Apr 25, 2022 · Welcome to the world of Hazm, a versatile toolkit designed specifically for Natural Language Processing (NLP) tasks involving Persian text. aufkd, 6wb3, sxic, 1h9w, mwa2, eedxxo, n7bw, kt8n5y, lnugol, se3ot,