spaCy - Industrial-strength Natural Language Processing in Python
Get things done spaCy is designed to help you do real work — to build real products, or gather real insights. The library respects your time, and tries to avoid wasting it. It's easy to install, and its API is simple and productive. Blazing fast spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to
CRFsuite - A fast implementation of Conditional Random Fields (CRFs)
CRFsuite is an implementation of Conditional Random Fields (CRFs) [Lafferty 01][Sha 03][Sutton] for labeling sequential data. Among the various implementations of CRFs, this software provides following features. Fast training and tagging. The primary mission of this software is to train and use CRF models as fast as possible. See the benchmark result for more information. Simple data format for tr
CRF++: Yet Another CRF toolkit
Template type Note also that there are two types of templates. The types are specified with the first character of templates. Unigram template: first character, 'U' This is a template to describe unigram features. When you give a template "U01:%x[0,1]", CRF++ automatically generates a set of feature functions (func1 ... funcN) like: func1 = if (output = B-NP and feature="U01:DT") return 1 else ret
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GitHub - nlpcloud/nlpcloud-python: NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and
GitHub - nihongodera/limelight: A php Japanese language text analyzer and parser.
