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International Conference on Intelligent Text Processing and Computational Linguistics

CICLing 2015: Computational Linguistics and Intelligent Text Processing pp 310–334Cite as

A Unified Framework to Identify and Extract Uncertainty Cues, Holders, and Scopes in One Fell-Swoop

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9041))

Abstract

We present a unified framework based on supervised sequence labelling methods to identify and extract uncertainty cues, holders, and scopes in one-fell swoop with an application on Arabic tweets. The underlying technology employs Support Vector Machines with a rich set of morphological, syntactic, lexical, semantic, pragmatic, dialectal, and genre-specific features, and yields an average F1 score of 0.759.

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Author information

Authors and Affiliations

  1. Department of Linguistics and Beckman Institute, University of Illinois Urbana-Champaign, Champaign, USA

    Rania Al-Sabbagh & Roxana Girju

  2. Graduate School of Library and Information Science, University of Illinois Urbana-Champaign, Champaign, USA

    Jana Diesner

Authors
  1. Rania Al-Sabbagh
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  2. Roxana Girju
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  3. Jana Diesner
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Corresponding author

Correspondence to Rania Al-Sabbagh .

Editor information

Editors and Affiliations

  1. Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico DF, Mexico

    Alexander Gelbukh

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Al-Sabbagh, R., Girju, R., Diesner, J. (2015). A Unified Framework to Identify and Extract Uncertainty Cues, Holders, and Scopes in One Fell-Swoop. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9041. Springer, Cham. https://doi.org/10.1007/978-3-319-18111-0_24

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  • DOI: https://doi.org/10.1007/978-3-319-18111-0_24

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18110-3

  • Online ISBN: 978-3-319-18111-0

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