Research Associate: CITANDA Post-Graduate Section Head Department of Information Systems Phone: (+27)-(0)21-6504256 Fax: (+27)-(0)21-6502280 Office: Leslie Commerce 4.21 >>> Linas Vepstas [EMAIL PROTECTED]> 2007/11/05 23:41 >> ( mailto:[EMAIL >>> PROTECTED]> ) >Do you have any recommendations for other parsers? One of the reasons I like Python: It's got NLTK and MontyLingua ( file:///C:/AC/Software/MontyLingua/MontyLingua.html#MontyLingua ): - MontyTokenizer - normalizes punctuation, spacing and contractions, with sensitivity to abbrevs. - MontyTagger - Part-of-speech tagging using PENN TREEBANK tagset - enriched with "Common Sense" from the Open Mind Common Sense project - MontyREChunker - chunks tagged text into verb, noun, and adjective chunks (VX,NX, and AX respectively) - MontyExtractor - extracts verb-argument structures, phrases, and other semantically valuable information from sentences and returns sentences as "digests" - MontyLemmatiser - part-of-speech sensitive lemmatisation - strips plurals (geese-->goose) and tense (were-->be, had-->have) - includes regexps from Humphreys and Carroll's morph.lex, and UPENN's XTAG corpus - MontyNLGenerator - generates summaries - generates surface form sentences - determines and numbers NPs and tenses verbs - accounts for sentence_type Note: It also has chatterbot code.
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