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    <titleInfo>
        <title>Natural intelligence in a machine translation system</title>
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        <namePart type="given">Howard</namePart>
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            <title>Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: System Descriptions</title>
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            <namePart type="given">Stephen</namePart>
            <namePart type="given">D</namePart>
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    <abstract>Any-Language Communications has developed a novel semantics-oriented pre-market prototype system, based on the Theory of Universal Grammar, that uses the innate relationships of the words in a sensible sentence (the natural intelligence) to determine the true contextual meaning of all the words. The system is built on a class/category structure of language concepts and includes a weighted inheritance system, a number language word conversion, and a tailored genetic algorithm to select the best of the possible word meanings. By incorporating all of the language information within the dictionaries, the same semantic processing code is used to interpret any language. This approach is suitable for machine translation (MT), sophisticated text mining, and artificial intelligence applications. An MT system has been tested with English, French, German, Hindi, and Russian. Sentences for each of those languages have been successfully interpreted and proper translations generated.</abstract>
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        <url>https://aclanthology.org/2002.amta-systems.3/</url>
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        <date>2002-oct 8-12</date>
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            <start>224</start>
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%0 Conference Proceedings
%T Natural intelligence in a machine translation system
%A Bender, Howard J.
%Y Richardson, Stephen D.
%S Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: System Descriptions
%D 2002
%8 oct 8 12
%I Springer
%C Tiburon, USA
%F bender-2002-natural
%X Any-Language Communications has developed a novel semantics-oriented pre-market prototype system, based on the Theory of Universal Grammar, that uses the innate relationships of the words in a sensible sentence (the natural intelligence) to determine the true contextual meaning of all the words. The system is built on a class/category structure of language concepts and includes a weighted inheritance system, a number language word conversion, and a tailored genetic algorithm to select the best of the possible word meanings. By incorporating all of the language information within the dictionaries, the same semantic processing code is used to interpret any language. This approach is suitable for machine translation (MT), sophisticated text mining, and artificial intelligence applications. An MT system has been tested with English, French, German, Hindi, and Russian. Sentences for each of those languages have been successfully interpreted and proper translations generated.
%U https://aclanthology.org/2002.amta-systems.3/
%P 224-228

Markdown (Informal)

[Natural intelligence in a machine translation system](https://aclanthology.org/2002.amta-systems.3/) (Bender, AMTA 2002)

• Natural intelligence in a machine translation system (Bender, AMTA 2002)

ACL

• Howard J. Bender. 2002. Natural intelligence in a machine translation system. In Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: System Descriptions, pages 224–228, Tiburon, USA. Springer.