Download IATE as a Resource for Teaching Names in the Translation and Interpreting Classroom

Author:

Sánchez Rodas FernandoORCID,Corpas Pastor GloriaORCID

Abstract

Proper names are a minoritarian yet fairly controversial topic in translation and interpreting literature. Some authors believe that they have been traditionally disregarded, becoming «one of translation’s coziest fortresses» (Albin, 2003); however, a number of prominent translation and interpreting scholars have explicitly studied proper names (Hermans, 1988; Moya Jiménez, 2001; Nord, 2003), and a stream of recent publications underline the challenge they represent in fields as varied as biomedicine (Cariello et al., 2021), literature (Jouini, 2020; Sarmaşık, 2022) and the law (Tang, 2021), among others. This paper proposes the integration of terminology databases and onomastics for interpreter and translator training. We will adopt a constructionist approach (cf. Goldberg, 1995). The download functionality of the terminology management system IATE is employed to extract a reliable English-Spanish dataset of 3,997 organization names, which is first analyzed in a quantitative-qualitative manner, and then exploited to design three templates (easy, medium, and advanced) aimed at bilingual naming practice. Results show a generally rich and robust dataset, with 96% cascading domain names, 66% marked as very reliable and only 8% as deprecated or obsolete. By contrast, most names (75%) were labelled as terms, which shows no consideration for their onymic nature and small or no relevance of other specialized knowledge representations (abbreviations, phrases, short terms, and non-linguistic forms). The proposed templates extensively develop a Goldbergian-style notation system for construction, and their flexibility and replicability make them a good candidate for automatization and/or combination with documentation resources and NLP-based tools throughout the learning process.

Publisher

Ediciones Universidad de Salamanca

Subject

General Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3