Scrap and parse text data from a webpage and make triple Knowledge Graph data.
Triples are generated based on pre-trained SpaCy's dependency tagging.
Triples are saved as a cvs file in data/ and a graph is generated.
- To run:
- Install python3.7 and the required packages
conda create -n k-g python=3.7 pip
python -m pip install -r requirements.txt
python knowledge_graph.py (optional argument)
(optional arguments):
-h, --help show a help message and exit
-f, --from-file Give a file path and draw a Knowledge Graph plot from the file.
--no-graph Do not draw a graph.
--no-save Do not save a triple data as a file.
-u, --url Provide an URL containing text to parse.
-s, --source Draw a Knowledge Graph only for the given source words.
-t, --target Draw a Knowledge Graph only for the given target words.
-e, --edge Draw a Knowledge Graph only for the given edge words.
-f, --with-file Provide a recording file rather than record
(source, target, edge arguments can take multiple words.)
- A graph example for London Wikipedia page where edges are one of
["is","was","are","were","been"]:
