chaine 1.1.3

Linear-chain conditional random fields for natural language processing

Chaine

Linear-chain conditional random fields for natural language processing.

Chaine is a modern Python library without third-party dependencies and a backend written in C. You can train conditional random fields for natural language processing tasks like named entity recognition.

• Lightweight: No use of bloated third-party libraries.
• Fast: Performance critical parts are written in C and thus blazingly fast.
• Easy to use: Designed with special focus on usability and a beautiful high-level API.

You can install the latest stable version from PyPI:

$ pip install chaine

Please refer to the introducing paper by Lafferty et al. for the theoretical concepts behind conditional random fields.

Minimal working example

>>> import chaine
>>> tokens = [["John", "Lennon", "was", "born", "in", "Liverpool"]]
>>> labels = [["B-PER", "I-PER", "O", "O", "O", "B-LOC"]]
>>> model = chaine.train(tokens, labels, max_iterations=5)
>>> model.predict(tokens)
[['B-PER', 'I-PER', 'O', 'O', 'O', 'B-LOC']]

Check out the examples for a more real-world use case.

Credits

This project makes use of and is partially based on:

• CRFsuite
• libLBFGS
• python-crfsuite
• sklearn-crfsuite