Syntax-Semantics Interaction Parsing Strategies. Inside SYNTAGMA
This addresses parsing challenges in NLP, but appears incremental as it builds on existing rule-based approaches.
The paper tackles syntactic ambiguity reduction and word sense disambiguation in NLP by introducing SYNTAGMA, a rule-based system that uses syntax-semantics interaction for selective parsing, resulting in coherent and accurate text interpretations.
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.