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The software annotates text with 41 broad semantic categories (Wordnet supersenses) for both nouns and verbs; i.e., it performs both sense disambiguation and named-entity recognition. The tagger implements a discriminatively-trained Hidden Markov Model.
OCR c++ library. Include: contour recognition; vectorisation; matrix letter feature recognition; auto page segmentation and detect rotation; SS3 ASM core; XML base; web-based GUI; 99,6% printed Unicode textrecognition; letter base up to 1200 letters.