TBLTools is a set of GATE processing resources that implements the Fast Transformation Based Learning Algorithm. You can train it to learn rules for NLP tasks such as Named Entity Recognition and Shallow parsing.
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* TBLTrainer.bestRule() choose rule with lower bad counts when two rules has the same score. * New package structure. * A hack was programed in Trainer. Now reinitialize the process when there are too many rules. Memory and execution time is better now. * Now, Trainer only erase the rules that are new and its good count is zero. * Files are saved with the given encoding. * ASName parameter in DocumentConverter resource added. * In Lexicon LR, key and classification initial parameters were added. Now it is possible to overwrite the mapping rule key => classification loaded from lexicon file (first line) * In Initial Tagger, lowerCase and uppInitial initial parameters were added. These are used to annotate unseen attributes (not in lexicon) * Trainer and CreateLexicon now can be executed at the end of a corpus pipeline. This helps preprocessing corpus with other gate pr's in a faster way. In order to add this functionality, the classes DocumentAnnotationManager and CorpusAnnotationManager were added (they both implement the new interface AnnotationManager). * Fixed bug in Lexicon.java there was a problem with the complex matcher regexp * Now DocumentConverter can read and convert all files in a directory (no recursion supported) so that you can load a whole corpus
* TBLTrainer.bestRule() choose rule with lower bad counts when two rules has the same score. * New package structure. * A hack was programed in Trainer. Now reinitialize the process when there are too many rules. Memory and execution time is better now. * Now, Trainer only erase the rules that are new and its good count is zero. * Files are saved with the given encoding. * ASName parameter in DocumentConverter resource added. * In Lexicon LR, key and classification initial parameters were added. Now it is possible to overwrite the mapping rule key => classification loaded from lexicon file (first line) * In Initial Tagger, lowerCase and uppInitial initial parameters were added. These are used to annotate unseen attributes (not in lexicon) * Trainer and CreateLexicon now can be executed at the end of a corpus pipeline. This helps preprocessing corpus with other gate pr's in a faster way. In order to add this functionality, the classes DocumentAnnotationManager and CorpusAnnotationManager were added (they both implement the new interface AnnotationManager). * Fixed bug in Lexicon.java there was a problem with the complex matcher regexp * Now DocumentConverter can read and convert all files in a directory (no recursion supported) so that you can load a whole corpus
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