Linguistic Inspired Graph Analysis

TL;DR

This paper explores the limitations of current graph structures in representing semantic and pragmatic information, proposing that enriching graphs could improve understanding and manipulation of complex linguistic data.

Contribution

It introduces a mapping between linguistic metamodels and graph theory, highlighting the need for new constructs to encode semantic and pragmatic information in graphs.

Findings

Current graphs lack constructs for semantic/pragmatic info

Enriching graphs could improve understanding of source structures

Further research needed to develop enriched graph models

Abstract

Isomorphisms allow human cognition to transcribe a potentially unsolvable problem from one domain to a different domain where the problem might be more easily addressed. Current approaches only focus on transcribing structural information from the source to target structure, ignoring semantic and pragmatic information. Functional Language Theory presents five subconstructs for the classification and understanding of languages. By deriving a mapping between the metamodels in linguistics and graph theory it will be shown that currently, no constructs exist in canonical graphs for the representation of semantic and pragmatic information. It is found that further work needs to be done to understand how graphs can be enriched to allow for isomorphisms to capture semantic and pragmatic information. This capturing of additional information could lead to understandings of the source structure and enhanced manipulations and interrogations of the contained relationships. Current mathematical graph structures in their general definition do not allow for the expression of higher information levels of a source.