Word segmentation granularity in Korean

TL;DR

This paper analyzes various levels of word segmentation granularity in Korean, revealing that separating only functional morphemes yields optimal parsing performance, challenging previous standards.

Contribution

It provides a detailed analysis of segmentation granularity levels in Korean and identifies the most effective approach for phrase structure parsing.

Findings

Separating only functional morphemes improves parsing accuracy.

Different segmentation granularities have distinct impacts on processing tasks.

The optimal granularity contradicts previous standard practices.

Abstract

This paper describes word {segmentation} granularity in Korean language processing. From a word separated by blank space, which is termed an eojeol, to a sequence of morphemes in Korean, there are multiple possible levels of word segmentation granularity in Korean. For specific language processing and corpus annotation tasks, several different granularity levels have been proposed and utilized, because the agglutinative languages including Korean language have a one-to-one mapping between functional morpheme and syntactic category. Thus, we analyze these different granularity levels, presenting the examples of Korean language processing systems for future reference. Interestingly, the granularity by separating only functional morphemes including case markers and verbal endings, and keeping other suffixes for morphological derivation results in the optimal performance for phrase structure parsing. This contradicts previous best practices for Korean language processing, which has been the de facto standard for various applications that require separating all morphemes.