most citedAspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CL2020★ 2 cited

Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios

Daniel Torregrosa, Nivranshu Pasricha, Maraim Masoud +4

Rule-based machine translation is a machine translation paradigm where linguistic knowledge is encoded by an expert in the form of rules that translate text from source to target l…