With the overall annotation agreement per variable ranging from 85% to 97.5%, we find that our automatic annotation strategies are very accurate.
we adapt our systems at two levels: First, we create category-specific language models by interpolating our general movie dialogue language model with a language model trained on only the most relevant subset of the bitext's target side.