Semantic Classification for Practical Natural Language Processing

Kavi Mahesh, Sergei Nirenburg

Abstract


In the field of natural language processing (NLP) there is now a consensus that all NLP systems that seek to represent and manipulate meanings of texts need an ontology, that is a taxonomic classification of concepts in the world to be used as semantic primitives. In our continued efforts to build a multilingual knowledge-based machine translation (KBMT) system using an interlingual meaning representation, we have developed an ontology to facilitate natural language interpretation and generation. The central goal of the Mikrokosmos project is to develop a computer system that produces a comprehensive Text Meaning Representation (TMR) for an input text in any of a set of source languages. Knowledge that supports this process is stored both in language-specific knowledge sources (such as a lexicon) and in an independently motivated, language-neutral ontology of concepts in the world.

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DOI: http://dx.doi.org/10.7152/acro.v6i1.12663