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.
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.
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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.
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26
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3
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jul 24, 2025
Commits (30d)
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