Exploiting multi-word units in history-based probabilistic generation
Hogan, Deirdre and Cafferkey, Conor and Cahill, Aoife and van Genabith, Josef (2007) Exploiting multi-word units in history-based probabilistic generation. In: EMNLP-CoNLL 2007 - Joint Meeting of the Conference on Empirical Methods in Natural Language Processing and the Conference on Computational Natural Language Learning, 28-30 June 2007, Prague, Czech Republic.
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We present a simple history-based model for sentence generation from LFG f-structures, which improves on the accuracy of previous models by breaking down PCFG independence assumptions so that more f-structure conditioning context is used in the prediction of grammar rule expansions. In addition, we present work on experiments with named entities and other multi-word units,
showing a statistically significant improvement of generation accuracy. Tested on section 23 of the PennWall Street Journal Treebank, the techniques described in this paper improve BLEU scores from 66.52 to 68.82, and coverage from 98.18% to 99.96%.
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