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KLUE: Korean Language Understanding Evaluation
TLDR
KLUE is a collection of 8 Korean natural language understanding tasks, including Topic Classification, Semantic Textual Similarity, Natural Language Inference, Named Entity Recognition, Relation Extraction, Dependency Parsing, Machine Reading Comprehension, and Dialogue State Tracking, and a comprehensive documentation on creating KLUE will facilitate creating similar resources for other languages in the future.
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Building Korean Abstract Meaning Representation Corpus
To explore the potential sembanking in Korean and ways to represent the meaning of Korean sentences, this paper reports on the process of applying Abstract Meaning Representation to Korean, a…
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Enhancing Universal Dependencies for Korean
TLDR
This paper proposes a modified method for mapping Korean Part-of-Speech (POS) tagset in relation to Universal Part- of-Speeches (UPOS) tag set in order to enhance the Universal Dependencies for the Korean Language.
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Annotation Issues in Universal Dependencies for Korean and Japanese
To investigate issues that arise in the process of developing a Universal Dependency (UD) treebank for Korean and Japanese, we begin by addressing the typological characteristics of Korean and…
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Analysis of the Penn Korean Universal Dependency Treebank (PKT-UD): Manual Revision to Build Robust Parsing Model in Korean
TLDR
The error analysis demonstrates that this revision of PKT-UD allows the parsing model to learn relations more robustly, reducing several critical errors that used to be made by the previous model.
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Crowdsourcing in the Development of a Multilingual FrameNet: A Case Study of Korean FrameNet
TLDR
This work investigated cross-lingual issues in crowdsourcing approaches for multilingual FrameNets, specifically in the context of the newly constructed Korean FrameNet and found that by allowing the crowd workers to make intuitive choices, they achieved a quality comparable to that of trained FrameNet experts.
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Universal POS Tagset for Korean
The Universal Dependencies(이하 UD)는 병렬 언어 처 리를 위해 여러 언어에 적용할 수 있는 형태적, 구문론 적 특성을 찾는 것을 목표로 하고 있다. 이를 위해 개별 언어가 가지고 있는 여러 언어 자원을 하나의 통일된 형 식(CoNLL U-Format)으로 변환하여 범언어적인 언어 처리 가 용이하도록 만들고 있다. UD 홈페이지에는…
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Korean Abstract Meaning Representation (AMR) Guidelines and Corpus for Graph-structured Meaning Representations
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Enhancing Quality of Corpus Annotation: Construction of the Multi-Layer Corpus Annotation and Simplified Validation of the Corpus Annotation
TLDR
Based on the validation results, the tendency of annotation across the entire corpus is observed macroscopically, and the corpus annotation validation results are analyzed microscopically to verify the validation methodology to address the case study.
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