no code implementations • LREC 2012 • Khalid Choukri, Victoria Arranz, Olivier Hamon, Jungyeul Park
This paper describes the International Standard Language Resource Number (ISLRN), a new identification schema for Language Resources where a Language Resource is provided with a unique and universal name using a standardized nomenclature.
no code implementations • WS 2012 • YoungGyun Hahm, Kyungtae Lim, Jungyeul Park, Yongun Yoon, Key-Sun Choi
no code implementations • LREC 2014 • Younggyun Hahm, Jungyeul Park, Kyungtae Lim, Youngsik Kim, Dosam Hwang, Key-Sun Choi
In this paper, we propose a novel method to automatically build a named entity corpus based on the DBpedia ontology.
no code implementations • 22 Jan 2015 • Jungyeul Park, Mouna Chebbah, Siwar Jendoubi, Arnaud Martin
The probabilistic HMMs have been one of the most used techniques based on the Bayesian model.
1 code implementation • CONLL 2017 • Ryan Hornby, Clark Taylor, Jungyeul Park
This paper describes UALing{'}s approach to the \textit{CoNLL 2017 UD Shared Task} using corpus selection techniques to reduce training data size.
no code implementations • WS 2017 • Jungyeul Park, Lo{\"\i}c Dugast, Jeen-Pyo Hong, Chang-Uk Shin, Jeong-Won Cha
We propose a novel method to bootstrap the construction of parallel corpora for new pairs of structurally different languages.
no code implementations • JEPTALNRECITAL 2018 • Jungyeul Park
Cet article traite des analyses d{'}erreurs quantitatives et qualitatives sur les r{\'e}sultats de l{'}analyse syntaxique des constituants pour le fran{\c{c}}ais.
no code implementations • JEPTALNRECITAL 2018 • Jungyeul Park
Cet article pr{\'e}sente une t{\^a}che du benchmarking de la reconnaissance de l{'}entit{\'e} nomm{\'e}e (REN) pour le fran{\c{c}}ais.
no code implementations • JEPTALNRECITAL 2018 • Jungyeul Park
Nous proposons trois nouvelles m{\'e}thodes pour construire et optimiser des plongements de mots pour le fran{\c{c}}ais.
no code implementations • WS 2019 • Mengyang Qiu, Jungyeul Park
The quantity and quality of training data plays a crucial role in grammatical error correction (GEC).
1 code implementation • WS 2019 • Jungyeul Park, Francis Tyers
In this paper we present a new annotation scheme for the Sejong part-of-speech tagged corpus based on Universal Dependencies style annotation.
no code implementations • WS 2019 • Mengyang Qiu, Xuejiao Chen, Maggie Liu, Krishna Parvathala, Apurva Patil, Jungyeul Park
In this paper, we explore two approaches of generating error-focused phrases and examine whether these phrases can lead to better performance in grammatical error correction for the restricted track of BEA 2019 Shared Task on GEC.
1 code implementation • COLING 2022 • Yige Chen, Eunkyul Leah Jo, Yundong Yao, Kyungtae Lim, Miikka Silfverberg, Francis M. Tyers, Jungyeul Park
In this study, we propose a morpheme-based scheme for Korean dependency parsing and adopt the proposed scheme to Universal Dependencies.
1 code implementation • 10 May 2023 • Eunkyul Leah Jo, Kyuwon Kim, Xihan Wu, Kyungtae Lim, Jungyeul Park, Chulwoo Park
This dataset adopts morphological feature schema from Sylak-Glassman et al. (2015) and Sylak-Glassman (2016) for the Korean language as we extract inflected verb forms from the Sejong morphologically analyzed corpus that is one of the largest annotated corpora for Korean.
no code implementations • 10 May 2023 • Yige Chen, Kyungtae Lim, Jungyeul Park
In the paper, we propose a novel way of improving named entity recognition in the Korean language using its language-specific features.
no code implementations • 29 May 2023 • Zhiyi Li, Shengjie Zhang, Yujie Song, Jungyeul Park
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.
no code implementations • 7 Sep 2023 • Jungyeul Park, Mija Kim
This paper describes word {segmentation} granularity in Korean language processing.
no code implementations • 24 Feb 2024 • Jungyeul Park, Mengyang Qiu
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.
no code implementations • 24 Feb 2024 • Min Zeng, Jiexin Kuang, Mengyang Qiu, Jayoung Song, Jungyeul Park
The writing examples of English language learners may be different from those of native speakers.
no code implementations • 27 Feb 2024 • Izia Xiaoxiao Wang, Xihan Wu, Edith Coates, Min Zeng, Jiexin Kuang, Siliang Liu, Mengyang Qiu, Jungyeul Park
The utilization of technology in second language learning and teaching has become ubiquitous.