Metonymy

Abstract

In this article we outline a basic approach to treating metonymy properly in a multilingual machine translation system. This is the first attempt at treating metonymy in an machine translation environment. The approach is guided by the differences of acceptability of metonymy which were obtained by our comparative survey among three languages, English, Chinese, and Japanese.The characteristics of the approach are as follows:(1) Influences of the context, individuals, and familiality with metonymy are not used. (2) An actual acceptability of each metonymic expression is not realized directly. (3) Grouping metonymic examples into patterns is determined by the acceptability judgement of the speakers surveyed as well as the analysts' intuition. (4) The analysis and generation components treat metonymy differently using the patterns. (5) The analysis component accepts a wider range of metonymy than the actual results of the survey, and the generation component treats metonymy more strictly than the actual results. We think that the approach is a starting point for more sophisticated approaches to translation in a multilirtgual machine translation environment.

An empirical study of incorporating syntactic constraints into BERT-based location metonymy resolution

“…MR attempts to distinguish the word with metonymic usage from literal usage given that word in an input sentence, typically location or organisation names. MR has been shown to be potentially helpful for various NLP applications such as machine translation (Kamei and Wakao 1992), relation extraction (RE) (Chan and Roth 2011) and geographical parsing (Monteiro, Davis, and Fonseca 2016;Gritta et al 2017;Li et al 2020). While other types of metonymies exist, in this paper, we are only interested in a specific type of conventional (regular) metonymy, namely, location metonymy.…”