Syntax-Semantics Interaction Parsing Strategies. Inside SYNTAGMA

TL;DR

This paper presents SYNTAGMA, a rule-based NLP system that effectively reduces syntactic ambiguity and disambiguates word senses through an innovative interaction between syntax and semantics, with detailed system architecture and resources.

Contribution

It introduces a novel interaction-based parsing strategy that enhances syntactic and semantic integration for more accurate natural language understanding.

Findings

Effective syntactic ambiguity reduction demonstrated

Improved word sense disambiguation achieved

Coherent and accurate text interpretation produced

Abstract

This paper discusses SYNTAGMA, a rule based NLP system addressing the tricky issues of syntactic ambiguity reduction and word sense disambiguation as well as providing innovative and original solutions for constituent generation and constraints management. To provide an insight into how it operates, the system's general architecture and components, as well as its lexical, syntactic and semantic resources are described. After that, the paper addresses the mechanism that performs selective parsing through an interaction between syntactic and semantic information, leading the parser to a coherent and accurate interpretation of the input text.