Dependency Parsing - Models and Evaluation: Investigating models and evaluation metrics for dependency parsing, which analyzes the grammatical structure of sentences to identify relationships

Abstract

Dependency parsing is a crucial task in natural language processing, aiming to analyze the syntactic structure of sentences by identifying dependencies between words. This paper provides a comprehensive review of various models and evaluation metrics used in dependency parsing. We discuss the evolution of dependency parsing models from early approaches to state-of-the-art neural network-based models. Furthermore, we explore different evaluation metrics and datasets commonly used to assess the performance of dependency parsers. By analyzing the strengths and weaknesses of existing models and evaluation techniques, this paper aims to provide insights into the current trends and future directions in dependency parsing research.