Evaluating RBMT output for -ing forms: A study of four target languages

Abstract

-ing forms in English are reported to be problematic for Machine Translation and are often the focus of rules in Controlled Language rule sets. We investigated how problematic -ing forms are for an RBMT system, translating into four target languages in the IT domain. Constituent-based human evaluation was used and the results showed that, in general, -ing forms do not deserve their bad reputation. A comparison with the results of five automated MT evaluation metrics showed promising correlations. Some issues prevail, however, and can vary from target language to target language. We propose different strategies for dealing with these problems, such as Controlled Language rules, semi-automatic post-editing, source text tagging and "post-editing" the source text.