A Chart-Parsing Algorithm for Efficient Semantic Analysis

TL;DR

This paper introduces a chart-parsing algorithm for semantic analysis of sequences of semantic units, significantly improving efficiency by reducing computation time from hyperexponential to polynomial, suitable for grammar-independent input interpretation.

Contribution

It presents a novel chart-parsing inspired algorithm for semantic analysis that operates efficiently on grammar-independent input sequences.

Findings

Reduces semantic analysis time from hyperexponential to polynomial.

Enables efficient interpretation of grammar-independent semantic units.

Applicable to systems using language-independent icons or similar inputs.

Abstract

In some contexts, well-formed natural language cannot be expected as input to information or communication systems. In these contexts, the use of grammar-independent input (sequences of uninflected semantic units like e.g. language-independent icons) can be an answer to the users' needs. A semantic analysis can be performed, based on lexical semantic knowledge: it is equivalent to a dependency analysis with no syntactic or morphological clues. However, this requires that an intelligent system should be able to interpret this input with reasonable accuracy and in reasonable time. Here we propose a method allowing a purely semantic-based analysis of sequences of semantic units. It uses an algorithm inspired by the idea of ``chart parsing'' known in Natural Language Processing, which stores intermediate parsing results in order to bring the calculation time down. In comparison with using declarative logic programming - where the calculation time, left to a prolog engine, is hyperexponential -, this method brings the calculation time down to a polynomial time, where the order depends on the valency of the predicates.