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Analysis Of Names Of Organic Chemical Compounds By Using Parser Combinators And The Generative Lexicon Theory

Author(s): Marcio de Souza Dias | Rita Maria Silva Julia | Eduardo Costa Pereira

Journal: International Journal of Artificial Intelligence & Applications
ISSN 0976-2191

Volume: 2;
Issue: 4;
Start page: 71;
Date: 2011;
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Keywords: Automatic Tutors for Organic Chemistry Nomenclature | Lexical Ambiguity | Computational Linguistics | Generative Lexicon Theory and Parser Combinators.

This work proposes OCLAS (Organic Chemistry Language Ambiguity Solver), an automatic system to analyze syntactically and semantically Organic Chemistry compound names and to generate the pictures of their chemical structures. If both parses detect that the input name corresponds to a theoreticallypossible organic chemical compound, the system generates its molecular structure picture, whether or not the name respects the current official nomenclature. This capacity of treating even names which, in spite of do not respect the constraints of the official nomenclatures, correspond to theoretically possible organic compound, represents an advance of OCLAS compared to other existing systems. OCLAS counts on the following tools: Generative Lexicon Theory (GLT), Parser Combinators and the Language Clean and an extension of the Xymtec package of Latex. The implemented system represents a helpful and friendly utilitarian as an automatic Organic Chemistry instructor.

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