Paper: Semantic Classification of Noun Phrases Using Web Counts and Learning Algorithms

ACL ID P07-3014
Title Semantic Classification of Noun Phrases Using Web Counts and Learning Algorithms
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors
  • Paul Nulty (University College Dublin, Dublin Ireland)

This paper investigates the use of machine learning algorithms to label modifier-noun compounds with a semantic relation. The attributes used as input to the learning algo- rithms are the web frequencies for phrases containing the modifier, noun, and a prepo- sitional joining term. We compare and evaluate different algorithms and different joining phrases on Nastase and Szpako- wicz’s (2003) dataset of 600 modifier-noun compounds. We find that by using a Sup- port Vector Machine classifier we can ob- tain better performance on this dataset than a current state-of-the-art system; even with a relatively small set of prepositional join- ing terms.