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flair - A very simple framework for state-of-the-art NLP

  •    Python

A very simple framework for state-of-the-art NLP. Developed by Zalando Research. A powerful syntactic-semantic tagger / classifier. Flair allows you to apply our state-of-the-art models for named entity recognition (NER), part-of-speech tagging (PoS), frame sense disambiguation, chunking and classification to your text.

nlpnet - A neural network architecture for NLP tasks, inspired in the SENNA system

  •    Python

Gitter is chat room for developers. nlpnet is a Python library for Natural Language Processing tasks based on neural networks. Currently, it performs part-of-speech tagging, semantic role labeling and dependency parsing. Most of the architecture is language independent, but some functions were specially tailored for working with Portuguese. This system was inspired by SENNA.

emnlp20_depsrl - Research code and scripts used in the paper Semantic Role Labeling as Syntactic Dependency Parsing

  •    Python

This repo contains the research code and scripts used in the paper Semantic Role Labeling as Syntactic Dependency Parsing. This README file aims at giving basic overviews of the code structure and its major components. For more questions, please directly contact the authors. The entrance point to the package is here. Calls to this package can be chained through fire CLI. The order of calling should usually be build-vocab, create-parser, load-embeddings, train and then finally finish. An example inference script is here using parser.evaluate(data) after loading in models and embeddings.






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