KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding

arXiv (2020)

초록

Natural language inference (NLI) and semantic textual similarity (STS) are key tasks in natural language understanding (NLU). Although several benchmark datasets for those tasks have been released in English and a few other languages, there are no publicly available NLI or STS datasets in the Korean language. Motivated by this, we construct and release new datasets for Korean NLI and STS, dubbed KorNLI and KorSTS, respectively. Following previous approaches, we machine-translate existing English training sets and manually translate development and test sets into Korean. To accelerate research on Korean NLU, we also establish baselines on KorNLI and KorSTS. Our datasets are made publicly available via our GitHub repository.

저자

함지연(카카오브레인), 최요중(카카오브레인), 박규병(카카오브레인), 최일지(카카오브레인), 소형준(카카오브레인)

키워드

NLP NLU Korean

발행 날짜

2020.04.07