Predicting relative prominence in noun-noun compounds

  • Authors:
  • Taniya Mishra;Srinivas Bangalore

  • Affiliations:
  • AT&T Labs-Research, Florham Park, NJ;AT&T Labs-Research, Florham Park, NJ

  • Venue:
  • HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

There are several theories regarding what influences prominence assignment in English noun-noun compounds. We have developed corpus-driven models for automatically predicting prominence assignment in noun-noun compounds using feature sets based on two such theories: the informativeness theory and the semantic composition theory. The evaluation of the prediction models indicate that though both of these theories are relevant, they account for different types of variability in prominence assignment.