Logical analysis of natural language semantics to solve the problem of computer understanding

TL;DR

This paper presents an object-oriented formal system using predicate calculus and semantic nets to improve natural language understanding, enabling more effective processing and problem-solving capabilities in computer understanding.

Contribution

It introduces a novel semantic net representation of natural language sentences combined with an object-oriented approach and knowledge bases for enhanced semantic analysis.

Findings

Semantic nets facilitate processing algorithms and object descriptions.

Predicate-based representation extends problem-solving capabilities.

Use of encyclopedic knowledge improves semantic understanding.

Abstract

An object--oriented approach to create a natural language understanding system is considered. The understanding program is a formal system built on the base of predicative calculus. Horn's clauses are used as well--formed formulas. An inference is based on the principle of resolution. Sentences of natural language are represented in the view of typical predicate set. These predicates describe physical objects and processes, abstract objects, categories and semantic relations between objects. Predicates for concrete assertions are saved in a database. To describe the semantics of classes for physical objects, abstract concepts and processes, a knowledge base is applied. The proposed representation of natural language sentences is a semantic net. Nodes of such net are typical predicates. This approach is perspective as, firstly, such typification of nodes facilitates essentially forming of processing algorithms and object descriptions, secondly, the effectiveness of algorithms is increased (particularly for the great number of nodes), thirdly, to describe the semantics of words, encyclopedic knowledge is used, and this permits essentially to extend the class of solved problems.