The original Brill tagger (in the AI repository)
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Description: Eric Brill's original trainable rule-based part-of-speech tagger, which is based on error-driven transformation-based learning (TBL). Comes with a model for English. Written in C (with some Perl code).
Package: areas/nlp/parsing/taggers/brill/ CMU Artificial Intelligence Repository Brill: Trainable Part of Speech Tagger This directory contains Eric Brill's trainable rule-based part of speech tagger. This tagger is based on transformation-based error-driven learning, a technique that has been effective in a number of natural language applications, including part of speech and word sense tagging, prepositional phrase attachment, and syntactic parsing. The code includes a tokenizer for ASCII English, an English lexicon enduced from the Brown corpus, a table of mappings for word suffixes to likely ambiguity classes, and an HMM trained on the odd numbered sentences in the Brown corpus. For more information, see chapter 6 of Brill's thesis.
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