Where's the Verb? Correcting Machine Translation During Question Answering

When a multi-lingual question-answering (QA) system provides an answer that has been incorrectly translated, it is very likely to be regarded as irrelevant. In this paper, we propose a novel method for correcting a deletion error that affects overall understanding of the sentence. Our post-editing technique uses information available at query time: examples drawn from related documents determined to be relevant to the query. Our results show that 4%-7% of MT sentences are missing the main verb and on average, 79% of the modified sentences are judged to be more comprehensible. The QA performance also benefits from the improved MT: 7% of irrelevant response sentences become relevant