TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation
Tense inconsistency frequently occurs in machine translation. However, there
are few criteria to assess the model's mastery of tense prediction from a
linguistic perspective. In this paper, we present a parallel tense test set,
containing French-English 552 utterances. We also introduce a corresponding
benchmark, tense prediction accuracy. With the tense test set and the
benchmark, researchers are able to measure the tense consistency performance of
machine translation systems for the first time.