Problem Formulation | Here, w is the estimated text, W* the gold-standard text, h is the estimated latent configuration of the model and h+ the oracle latent configuration. |
Problem Formulation | In other NLP tasks such as syntactic parsing, there is a gold-standard parse, that can be used as the oracle. |
Results | They broadly convey similar meaning with the gold-standard ; ANGELI exhibits some long-range repetition, probably due to reiteration of the same record patterns. |
Results | It is worth noting that both our system and ANGELI produce output that is semantically compatible with but lexically different from the gold-standard (compare please list the flights and show me the flights against give me the flights). |
Conclusion | Even though we have used a small set of gold-standard alignments to tune our hyperparameters, we found that performance was fairly robust to variation in the hyperparameters, and translation performance was good even when gold-standard alignments were unavailable. |
Experiments | We set the hyperparameters a and ,6 by tuning on gold-standard word alignments (to maximize F1) when possible. |
Experiments | First, we evaluated alignment accuracy directly by comparing against gold-standard word alignments. |