A unified framework for scope learning via simplified shallow semantic parsing

  • Authors:
  • Qiaoming Zhu;Junhui Li;Hongling Wang;Guodong Zhou

  • Affiliations:
  • Soochow University, Suzhou, China;Soochow University, Suzhou, China;Soochow University, Suzhou, China;Soochow University, Suzhou, China

  • Venue:
  • EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper approaches the scope learning problem via simplified shallow semantic parsing. This is done by regarding the cue as the predicate and mapping its scope into several constituents as the arguments of the cue. Evaluation on the BioScope corpus shows that the structural information plays a critical role in capturing the relationship between a cue and its dominated arguments. It also shows that our parsing approach significantly outperforms the state-of-the-art chunking ones. Although our parsing approach is only evaluated on negation and speculation scope learning here, it is portable to other kinds of scope learning.