Earticle

초록

영어

This study examines the characteristics and quality of machine translation (MT) for named entities (NEs). We first provided an overview of the underlying mechanisms and technical obstacles involved in NE translation, based on previous studies in this field to understand the challenges that MTs may encounter when translating NEs. Based on these theoretical considerations, we proposed three hypotheses regarding potential NE-related translation problems and error types: (1) MTs may struggle to translate NEs consistently; (2) MTs often fail to differentiate proper nouns from common nouns; and (3) without sufficient contextual support, low-frequency NEs may be translated incorrectly, resulting in non-words or semantically unrelated terms. We performed a statistical analysis of 120 translations produced by two standard MT systems (Google Translate and Papago) and two generative artificial intelligence models (ChatGPT 3.5 and ClovaX) to test these hypotheses. The results revealed that (1) consistency errors occurred in 4.21%–26%of all NE translations, (2) 19.55%–50.34% of proper nouns that could be confused with common nouns were incorrectly translated as such, and (3) 31.31%–35.72%of low-frequency NEs lacking sufficient context were mistranslated.

목차

Abstract
I. 들어가며
II. 기계는 개체명을 어떻게 번역하는가?
III. 개체명 번역은 왜 어려운가?
IV. 실험
1. 연구 질문
2. 분석자료
3. 분석틀
4. 분석자
V. 결과 및 분석
1. 전체 분석
2. 연구 가설 검증
VI. 결론
참고문헌

키워드

저자

• 정혜연 [ Chung, Hye-yeon | 한국외국어대학교 ] 1저자
• 최혜림 [ Choi, Hye-rim | 한국외국어대학교 ] 1저자
• 강상희 [ Kang, Sang-hee | 한국외국어대학교 ]
• 김선경 [ Kim, Sun-gyung | 한국외국어대학교 ]
• 무전 [ Mu, Zhen-zhen | 서울과학종합대학원대학교 ]
• 오주아 [ Oh, Ju-ah | 한국외국어대학교 ]
• 이예지 [ Lee, Ye-ji | 한국외국어대학교 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  통역과 번역 [Interpretation and Translation]

• 간기

  연3회

• pISSN

  1229-6074

• 수록기간

  1999~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 717 DDC 400