Search Results for author: Chang-Ki Lee

Found 4 papers, 0 papers with code

KNU-HYUNDAI's NMT system for Scientific Paper and Patent Tasks onWAT 2019

no code implementations WS 2019 Cheoneum Park, Young-Jun Jung, Kihoon Kim, Geonyeong Kim, Jae-Won Jeon, Seongmin Lee, Jun-Seok Kim, Chang-Ki Lee

In this paper, we describe the neural machine translation (NMT) system submitted by the Kangwon National University and HYUNDAI (KNU-HYUNDAI) team to the translation tasks of the 6th workshop on Asian Translation (WAT 2019).

Data Augmentation Machine Translation +1

ThisIsCompetition at SemEval-2019 Task 9: BERT is unstable for out-of-domain samples

no code implementations SEMEVAL 2019 Cheoneum Park, Juae Kim, Hyeon-gu Lee, Reinald Kim Amplayo, Harksoo Kim, Jungyun Seo, Chang-Ki Lee

This paper describes our system, Joint Encoders for Stable Suggestion Inference (JESSI), for the SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums.

Suggestion mining Translation +1

KNU CI System at SemEval-2018 Task4: Character Identification by Solving Sequence-Labeling Problem

no code implementations SEMEVAL 2018 Cheoneum Park, Heejun Song, Chang-Ki Lee

Character identification is an entity-linking task that finds words referring to the same person among the nouns mentioned in a conversation and turns them into one entity.

Coreference Resolution Entity Linking

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