We present a series of models for doing statistical machine translation based on labeled semantic dependency graphs. We describe how these models were employed to augment an existing example-based MT system, and present results showing that doing so led to a significant improvement in translation quality as measured by the BLEU metric.

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Publisher  ACL/SIGPARSE
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