Korean Named Entity Recognition Based on Language-Specific Features

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A3WQXAXJJ" target="_blank" >RIV/00216208:11320/23:3WQXAXJJ - isvavai.cz</a>

Result on the web

<a href="http://arxiv.org/abs/2305.06330" target="_blank" >http://arxiv.org/abs/2305.06330</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.48550/arXiv.2305.06330" target="_blank" >10.48550/arXiv.2305.06330</a>

Result language

angličtina

Original language name

Korean Named Entity Recognition Based on Language-Specific Features

Original language description

"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 efficiently recognizing named entities in Korean has hardly been explored. This is because the Korean language has distinct linguistic properties that prevent models from achieving their best performances. Therefore, an annotation scheme for {Korean corpora} by adopting the CoNLL-U format, which decomposes Korean words into morphemes and reduces the ambiguity of named entities in the original segmentation that may contain functional morphemes such as postpositions and particles, is proposed herein. We investigate how the named entity tags are best represented in this morpheme-based scheme and implement an algorithm to convert word-based {and syllable-based Korean corpora} with named entities into the proposed morpheme-based format. Analyses of the results of {statistical and neural} models reveal that the proposed morpheme-based format is feasible, and the {varied} performances of the models under the influence of various additional language-specific features are demonstrated. Extrinsic conditions were also considered to observe the variance of the performances of the proposed models, given different types of data, including the original segmentation and different types of tagging formats."

Czech name

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Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

"Natural Language Engineering"

ISSN

1351-3249

e-ISSN

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Volume of the periodical

""

Issue of the periodical within the volume

2023-6-13

Country of publishing house

US - UNITED STATES

Number of pages

44

Pages from-to

1-44

UT code for WoS article

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EID of the result in the Scopus database

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