This corpus-based research focuses on building a corpus of Indonesian children?s storybooks to find the frequent content words in order to identify Indonesian-core vocabulary for teaching English to Indonesian preschool children. The data was gathered from 131 Indo-nesian children?s storybooks, which resulted in a corpus of 134,320 words. These data were run through a frequency menu in MonoConc Pro, a corpus program. Data analysis was analyzed by selecting the frequent nouns, verbs, adjectives, and adverbs before each of them was lemmatized. The result showed that the children were already exposed to both ordinary and imaginative concepts, antonym in adjective, time reference, and compound nouns. The narrative discourse clearly influenced the kind of verbs the children exposed to.