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pro vyhledávání: '"Park, Jungyeul"'
Named entity recognition (NER) is a crucial task that aims to identify structured information, which is often replete with complex, technical terms and a high degree of variability. Accurate and reliable NER can facilitate the extraction and analysis
Externí odkaz:
http://arxiv.org/abs/2410.12750
Autor:
Song, Seohyun, Jo, Eunkyul Leah, Chen, Yige, Hong, Jeen-Pyo, Kim, Kyuwon, Wee, Jin, Kang, Miyoung, Lim, KyungTae, Park, Jungyeul, Park, Chulwoo
The Sejong dictionary dataset offers a valuable resource, providing extensive coverage of morphology, syntax, and semantic representation. This dataset can be utilized to explore linguistic information in greater depth. The labeled linguistic structu
Externí odkaz:
http://arxiv.org/abs/2410.01100
We introduce an evaluation system designed to compute PARSEVAL measures, offering a viable alternative to \texttt{evalb} commonly used for constituency parsing evaluation. The widely used \texttt{evalb} script has traditionally been employed for eval
Externí odkaz:
http://arxiv.org/abs/2405.14150
Autor:
Wang, Izia Xiaoxiao, Wu, Xihan, Coates, Edith, Zeng, Min, Kuang, Jiexin, Liu, Siliang, Qiu, Mengyang, Park, Jungyeul
The utilization of technology in second language learning and teaching has become ubiquitous. For the assessment of writing specifically, automated writing evaluation (AWE) and grammatical error correction (GEC) have become immensely popular and effe
Externí odkaz:
http://arxiv.org/abs/2402.17613
Autor:
Park, Jungyeul, Qiu, Mengyang
This paper introduces a novel perspective on the automated essay scoring (AES) task, challenging the conventional view of the ASAP dataset as a static entity. Employing simple text denoising techniques using prompting, we explore the dynamic potentia
Externí odkaz:
http://arxiv.org/abs/2402.15931
The writing examples of English language learners may be different from those of native speakers. Given that there is a significant differences in second language (L2) learners' error types by their proficiency levels, this paper attempts to reduce o
Externí odkaz:
http://arxiv.org/abs/2402.15930
Autor:
Park, Jungyeul, Kim, Mija
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 granula
Externí odkaz:
http://arxiv.org/abs/2309.03713
Biomedical named entity recognition (NER) is a critial task that aims to identify structured information in clinical text, which is often replete with complex, technical terms and a high degree of variability. Accurate and reliable NER can facilitate
Externí odkaz:
http://arxiv.org/abs/2305.18152
We present in this work a new Universal Morphology dataset for Korean. Previously, the Korean language has been underrepresented in the field of morphological paradigms amongst hundreds of diverse world languages. Hence, we propose this Universal Mor
Externí odkaz:
http://arxiv.org/abs/2305.06335
Publikováno v:
Nat. Lang. Eng. 30 (2024) 625-649
In the paper, we propose a novel way of improving named entity recognition in the Korean language using its language-specific features. While the field of named entity recognition has been studied extensively in recent years, the mechanism of efficie
Externí odkaz:
http://arxiv.org/abs/2305.06330