Natural Language Processing

nlpnet – Natural Language Processing with neural networks

nlpnet is a Python library for Natural Language Processing tasks based on neural networks. Currently, it performs part-of-speech tagging and semantic role labeling. It may be used as a Python library or through its standalone scripts.

Most of the architecture is language independent, but some functions were especially tailored for working with Portuguese.

This system was inspired by SENNA, but has some conceptual and practical differences.

Key Features

  • Performs POS tagging, SRL and dependency parsing.
  • Can be used both as a Python library or by its standalone scripts.
  • New models for POS and SRL can be trained using the nlpnet-train.py script.
  • Includes standalone scripts that may be called from a command line:
    • nlpnet-train – train a new model or further train an existing one.
    • nlpnet-load-embeddings – load word embeddings trained externally. It accepts different formats.
    • nlpnet-test – measure the performance of a model against a gold data set.
    • nlpnet-tag – call a model and tag some given text.

nlpnet requires NLTK and NumPy.

Website: github.com/erickrf/nlpnet
Support:
Developer: Erick Rocha Fonseca
License: MIT License

nlpnet is written in Python. Learn Python with our recommended free books and free tutorials.


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