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News Graph

Key information extration from text and graph visilization. Inspired by TextGrapher.

Project Introduction

How to represent a text in a simple way is a chanllenge topic. This peoject try to extraction key information from the text by NLP methods, which contain NER extraction, relation detection, keywords extraction, frequencies words extraction. And finally show the key information in a graph way.please read the blog for more in depth details. https://fir-speedboat-5ee.notion.site/Building-Knowledge-Graphs-Using-Python-82276798233c45e8a85280e4a9308a5c?pvs=25

  1. flow

Example Demo

  1. image1

  2. image1

image02

Node coloring

  • Red:Location
  • Blue:Person
  • Green:organization
  • Grey:other

usage

  1. Run main.py: This script will generate the graph_data.json file.
  2. Run main_kg.py: This script will generate the graph_data_kg.json file.
  3. Run difference.py: This script will compute the difference between the generated files.
  4. Run find_ner.py: This script will filter the data based on Named Entity Recognition (NER).
  5. Run ner_plot.py: This script will generate the HTML file for graph visualization .