Wapiti is a very fast CRF toolkit (written in C++) for segmenting and labeling items and sequence data written and maintained by Thomas Lavergne; Wapiti was developed within the CroTAL project.
Wapiti's implementation is described in
- T. Lavergne, O. Cappé, and F. Yvon. Practical Very Large Scale CRFs. In Proc. 48th Annual Meeting Association for Computational Linguistics (ACL), pages 504-513, Uppsala, Sweden, July 2010.
and is based, partly, on
- N. Sokolovska, T. Lavergne, O. Cappé, and F. Yvon. Efficient Learning of Sparse Conditional Random Fields for Supervised Sequence Labelling. IEEE J. Sel. Topics Signal Process., 4(6):953-964, December 2010.
Wapiti is also available from the public evaluation site MLcomp and its performance appears to be very good on the SequenceTagging tasks (best program from the repository on 5 of the 16 datasets as of August 2010).