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Our premise is that an intelligent system should be able to structure all the information that can be obtained from natural language text, and it should do it in such a manner that the structured information be useful for further processing. This paper presents an experiment in structuring information from the natural language incomplete descriptions of 101 animals collected from a children's dictionary...
This paper revises the classic Ontological Semantics theory with regard to the output of the analyzer. We argue that it is not enough to produce semantic interpretation of text, and syntactic trees should serve not only as clues for semantic processing but also as an output in its own right. We show that it is useful to combine both results of syntactic and semantic processing in a single output while...
Natural language understanding systems are increasingly needed for intuitive, efficient interaction with large information stores. The object-centered nature of these stores - that they encode states, attributes, and relationships of objects - may not be best served by the current verb-driven syntactic paradigm. We develop a highly-parallelizable noun-driven syntax in response, and evaluate its performance...
The paper makes a case for expanding the range of words that Computing With Words typically considers to, eventually, all the words in a natural language, thus accounting accurately for the inherent vagueness of natural language meaning and creating an overlap with computational semantics. The claim is illustrated with examples of a few English nouns and verbs rather than the usual adjectives and...
This paper describes the process of deriving the meaning of an unknown word within the framework of meaning based natural language processing. It uses the clues supplied by the rest of the sentence, taking into account various degrees of possibilities of what the unknown word can mean, according to the previously acquired knowledge resources. The process of finding the meaning is incremental, and...
The paper outlines a framework for a full incorporation of fuzziness into a comprehensive system of natural language meaning processing with the help of ontological semantic technology. It goes far beyond the traditional examples of fuzziness for natural language modifiers, claiming that fuzziness is pervasive throughout natural language and cannot be avoided without a considerable penalty on accuracy.
The paper analyzes multiple noun expressions, or compound nouns, as part of the implementation of Ontological Semantic Technology, which uses a lexicon, an ontology, and a semantic text analyzer to access and represent the meaning of text. Because the analysis and results depend on the lexical senses of words, general principles of lexical acquisition are discussed. The success in interpretation and...
Humor is everywhere, as long as you are willing to see it, both accidental and intentional. Computers have evolved from simple calculating machines to playing chess, controlling air and space flights, and talking to humans. They are increasingly used to informally gather information from humans using human language. The paper mentions that will a computer ever understand humor as well as we do? Some...
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