Issue #96 – Using Annotations for Machine Translating Named Entities
27 Aug20
Issue #96 – Using Annotations for Machine Translating Named Entities
Author: Dr. Carla Parra Escartín, Global Program Manager @ Iconic
Introduction
Getting the translation of named entities right is not a trivial task and Machine Translation (MT) has traditionally struggled with it. If a named entity is wrongly translated, the human eye will quickly spot it, and more often than not, those mistranslations will make people burst into laughter as machines can, seemingly, be very creative.
To a certain extent, named entities could be treated in MT the same way that we treat Terminology, another tricky field which we have tackled before in issues #7 (Terminology in Neural MT (NMT)) and #79 (Merging Terminology into Neural Machine Translation) of our blog series. In fact, in issue #79, one of the areas tackled in Wang et al. (2019) is precisely the translation of named entities.
In today’s issue we look into the work done by Modrzejewski et al. (2020), who explore whether incorporating external annotations improves the translation of named entities in NMT. Their approach consists of using a named entity recognition (NER) system to annotate the data prior