π« Industrial-strength Natural Language Processing (NLP) in Python
A very simple framework for state-of-the-art Natural Language Processing (NLP)
An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts)
π¦ Integrating LLMs into structured NLP pipelines
Local-first privacy guard: anonymize your documents before sharing with LLMs.
A suite of Arabic natural language processing tools developed by the CAMeL Lab at New York University Abu Dhabi.