Ecosystems:
spaCy
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
Example Demo
Node coloring
- Red:Location
- Blue:Person
- Green:organization
- Grey:other
usage
pip install -r requirements.txt
install the en_core_web_lg before running the scripts
python -m spacy download en_core_web_lg
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Run
main.py: This script will generate thegraph_data.jsonfile. -
Run
main_kg.py: This script will generate thegraph_data_kg.jsonfile. -
Run
difference.py: This script will compute the difference between the generated files. -
Run
find_ner.py: This script will filter the data based on Named Entity Recognition (NER). -
Run
ner_plot.py: This script will generate the HTML file for graph visualization .
Switch Branch and Review Interconnections Between Documents
Package Rankings
Top 34.84% on Pypi.org