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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.
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.