Why Find the Right One?

The present paper investigates the impact of the anaphoric one words in English on the Neural Machine Translation (NMT) process using English-Hindi as source and target language pair. As expected, the experimental results show that the state-of-the-art Google English-Hindi NMT system achieves significantly poorly on sentences containing anaphoric ones as compared to the sentences containing regular, non-anaphoric ones. But, more importantly, we note that amongst the anaphoric words, the noun class is clearly much harder for NMT than the determinatives. This reaffirms the linguistic disparity of the two phenomenon in recent theoretical syntactic literature, despite the obvious surface similarities.