Korean Dependency Parsing Using Deep Biaffine Dependency Parser

Dependency parsing is a fundamental component of natural language processing (NLP), crucial for various applications like machine translation, information retrieval, relation extraction, and question answering. Scholarly discourse often emphasizes the use of end-to-end, sequence-to-sequence neural network configurations for dependency parsing. This study focuses on evaluating the effectiveness of the Biaffine dependency parser for parsing Korean language dependencies. It aims to determine the parser’s ability to accurately and efficiently reveal the intricate syntactic relationships inherent in Korean linguistic structures.