urchade/GLiNER

💫 Industrial-strength Natural Language Processing (NLP) in Python

Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.

Minimal keyword extraction with BERT

A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.

CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.

LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows

Convert any text to a graph of knowledge. This can be used for Graph Augmented Generation or Knowledge Graph based QnA