neostrange/text2graphs

A Python framework for automating domain-agnostic and domain-specific Knowledge Graphs from unstructured text. Integrates NLP and Neo4j for entity extraction, relationship mapping, and semantic enrichment. Ideal for text mining and analytics, with support for temporal and event tagging.

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Emerging

This project helps domain experts and researchers automatically build organized knowledge bases from large amounts of unstructured text documents. It takes raw text, identifies key entities and relationships, and then structures this information into a connected network (a knowledge graph). The result is a searchable and analyzable graph database that reveals patterns, events, and temporal connections within your textual data.

No commits in the last 6 months.

Use this if you need to transform a collection of text documents into a structured, queryable knowledge graph to uncover insights, understand relationships, or track events and their timings.

Not ideal if you're looking for a simple text summarization tool or if you don't require deep semantic analysis and graph-based data representation.

text-mining knowledge-management semantic-analysis information-extraction natural-language-processing
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 10 / 25

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Stars

26

Forks

3

Language

Jupyter Notebook

License

MIT

Last pushed

Jul 24, 2025

Commits (30d)

0

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