Improving Korean NLP Tasks with Linguistically Informed Subword Tokenization and Sub-character Decomposition

Autor:	Jeon, Taehee, Yang, Bongseok, Kim, Changhwan, Lim, Yoonseob
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language 68T50
Druh dokumentu:	Working Paper
Popis:	We introduce a morpheme-aware subword tokenization method that utilizes sub-character decomposition to address the challenges of applying Byte Pair Encoding (BPE) to Korean, a language characterized by its rich morphology and unique writing system. Our approach balances linguistic accuracy with computational efficiency in Pre-trained Language Models (PLMs). Our evaluations show that this technique achieves good performances overall, notably improving results in the syntactic task of NIKL-CoLA. This suggests that integrating morpheme type information can enhance language models' syntactic and semantic capabilities, indicating that adopting more linguistic insights can further improve performance beyond standard morphological analysis. Comment: 10 pages, 3 figures, 5 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.03928 Zobrazit plný text záznamu View this record from Arxiv