renard-pipeline 0.4.2

Relationships Extraction from NARrative Documents

Renard

Renard (Relationships Extraction from NARrative Documents) is a library for creating and using custom character networks extraction pipelines. Renard can extract dynamic as well as static character networks.

Installation

You can install the latest version using pip:

pip install renard-pipeline

Currently, Renard supports Python 3.8, 3.9 and 3.10.

Documentation

Documentation, including installation instructions, can be found at https://compnet.github.io/Renard/

If you need local documentation, it can be generated using Sphinx. From the docs directory, make html should create documentation under docs/_build/html.

Tutorial

Renard's central concept is the Pipeline.A Pipeline is a list of PipelineStep that are run sequentially in order to extract a character graph from a document. Here is a simple example:

from renard.pipeline import Pipeline
from renard.pipeline.tokenization import NLTKTokenizer
from renard.pipeline.ner import NLTKNamedEntityRecognizer
from renard.pipeline.character_unification import GraphRulesCharacterUnifier
from renard.pipeline.graph_extraction import CoOccurrencesGraphExtractor

with open("./my_doc.txt") as f:
	text = f.read()

pipeline = Pipeline(
	[
		NLTKTokenizer(),
		NLTKNamedEntityRecognizer(),
		GraphRulesCharacterUnifier(min_appearance=10),
		CoOccurrencesGraphExtractor(co_occurrences_dist=25)
	]
)

out = pipeline(text)

For more information, see renard_tutorial.py, which is a tutorial in the jupytext format. You can open it as a notebook in Jupyter Notebook (or export it as a notebook with jupytext --to ipynb renard-tutorial.py).

Running tests

Renard uses pytest for testing. To launch tests, use the following command :

poetry run python -m pytest tests

Expensive tests are disabled by default. These can be run by setting the environment variable RENARD_TEST_ALL to 1.

Contributing

see the "Contributing" section of the documentation.