Universe

Kindred

Biomedical relation extraction using spaCy

Kindred is a package for relation extraction in biomedical texts. Given some training data, it can build a model to identify relations between entities (e.g. drugs, genes, etc) in a sentence.

Example

import kindred trainCorpus = kindred.bionlpst.load('2016-BB3-event-train') devCorpus = kindred.bionlpst.load('2016-BB3-event-dev') predictionCorpus = devCorpus.clone() predictionCorpus.removeRelations() classifier = kindred.RelationClassifier() classifier.train(trainCorpus) classifier.predict(predictionCorpus) f1score = kindred.evaluate(devCorpus, predictionCorpus, metric='f1score')
Author info

Jake Lever

GitHubjakelever/kindred

Categories standalone

Submit your project

If you have a project that you want the spaCy community to make use of, you can suggest it by submitting a pull request to the spaCy website repository. The Universe database is open-source and collected in a simple JSON file. For more details on the formats and available fields, see the documentation. Looking for inspiration your own spaCy plugin or extension? Check out the project idea label on the issue tracker.

Read the docsJSON source