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. If you use nlpnet, please cite one or both of the articles below, according to your needs (POS or SRL):

• Fonseca, E. R. and Rosa, J.L.G. A Two-Step Convolutional Neural Network Approach for Semantic Role Labeling. Proceedings of the 2013 International Joint Conference on Neural Networks, 2013. p. 2955-2961 [PDF]

• Fonseca, E. R. and Rosa, J.L.G. Mac-Morpho Revisited: Towards Robust Part-of-Speech Tagging. Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology, 2013. p. 98-107 [PDF]

Contents

• Introduction
  • Installation
  • Brief explanation
  • Basic usage
• Trained Models
  • Word Embeddings (Portuguese)
  • POS (Portuguese)
  • SRL (Portuguese)
  • Dependency and POS (English)
• Training
  • Importing Word Representations
  • Task specific training
• Standalone Scripts
  • nlpnet-tag
  • nlpnet-test
• Utility Functions
  • Module nlpnet.utils
• Networks
  • Module nlpnet.network