Beyond the pipeline: discrete optimization in NLP

  • Authors:
  • Tomasz Marciniak;Michael Strube

  • Affiliations:
  • EML Research gGmbH, Heidelberg, Germany;EML Research gGmbH, Heidelberg, Germany

  • Venue:
  • CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
  • Year:
  • 2005

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Abstract

We present a discrete optimization model based on a linear programming formulation as an alternative to the cascade of classifiers implemented in many language processing systems. Since NLP tasks are correlated with one another, sequential processing does not guarantee optimal solutions. We apply our model in an NLG application and show that it performs better than a pipeline-based system.