This paper describes how named entity (NE) classes can be used to improve broad coverage surface realization with the OpenCCG realizer. Our experiments indicate that collapsing certain multi-word NEs and interpolating a language model where NEs are replaced by their class labels yields the largest quality increase, with 4-grams adding a small additional boost. Substantial further benefit is obtained by including class information in the hypertagging (supertagging for realization) component of the system, yielding a state-of-theart BLEU score of 0.8173 on Section 23 of the CCGbank. A targeted manual evaluation confirms that the BLEU score increase corresponds to a significant rise in fluency.
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