Adapting a general parser to a sublanguage

TL;DR

This paper presents a method to adapt a general parser for biological sublanguages by leveraging terminology identification, text normalization, lexicon enhancements, and grammar rule adaptation to improve parsing accuracy.

Contribution

It introduces a comprehensive approach combining multiple strategies to tailor a general parser for specialized biological texts, enhancing parsing performance.

Findings

Improved parsing accuracy after adaptation

Effective use of terminology identification in parsing

Enhanced parser performance with combined strategies

Abstract

In this paper, we propose a method to adapt a general parser (Link Parser) to sublanguages, focusing on the parsing of texts in biology. Our main proposal is the use of terminology (identication and analysis of terms) in order to reduce the complexity of the text to be parsed. Several other strategies are explored and finally combined among which text normalization, lexicon and morpho-guessing module extensions and grammar rules adaptation. We compare the parsing results before and after these adaptations.