Hierarchical semantic role labeling

Alessandro Moschitti, Ana Maria Giuglea, Bonaventura Coppola, Roberto Basili

Research output: Contribution to conferencePaper

25 Citations (Scopus)

Abstract

We present a four-step hierarchical SRL strategy which generalizes the classical two-level approach (boundary detection and classification). To achieve this, we have split the classification step by grouping together roles which share linguistic properties (e.g. Core Roles versus Adjuncts). The results show that the nonoptimized hierarchical approach is computationally more efficient than the traditional systems and it preserves their accuracy.

Original languageEnglish
Pages201-204
Number of pages4
Publication statusPublished - 1 Dec 2005
Event9th Conference on Computational Natural Language Learning, CoNLL 2005 - Ann Arbor, MI, United States
Duration: 29 Jun 200530 Jun 2005

Other

Other9th Conference on Computational Natural Language Learning, CoNLL 2005
CountryUnited States
CityAnn Arbor, MI
Period29/6/0530/6/05

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Linguistics and Language

Cite this

Moschitti, A., Giuglea, A. M., Coppola, B., & Basili, R. (2005). Hierarchical semantic role labeling. 201-204. Paper presented at 9th Conference on Computational Natural Language Learning, CoNLL 2005, Ann Arbor, MI, United States.