NUS at the HOO 2012 shared task

  • Authors:
  • Daniel Dahlmeier;Hwee Tou Ng;Eric Jun Feng Ng

  • Affiliations:
  • NUS Graduate School for Integrative Sciences and Engineering;NUS Graduate School for Integrative Sciences and Engineering and National University of Singapore;National University of Singapore

  • Venue:
  • Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes the submission of the National University of Singapore (NUS) to the HOO 2012 shared task. Our system uses a pipeline of confidence-weighted linear classifiers to correct determiner and preposition errors. Our system achieves the highest correction F1 score on the official test set among all 14 participating teams, based on gold-standard edits both before and after revision.