CRF++: Yet Another CRF toolkit

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Description

CRF++ is a simple, customizable, and open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data. CRF++ is designed for generic purpose and will be applied to a variety of NLP tasks, such as Named Entity Recognition, Information Extraction and Text Chunking.

Features
Can redefine feature sets
Written in C++ with STL
Fast training based on LBFGS, a quasi-newton algorithm for large scale numerical optimization problem
Less memory usage both in training and testing
encoding/decoding in practical time
Can perform n-best outputs
Can perform single-best MIRA training
Can output marginal probabilities for all candidates
Available as an open source software