A Unified Framework to Identify and Extract Uncertainty Cues, Holders, and Scopes in One Fell-Swoop
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  • 作者：Rania Al-Sabbagh (14)
    Roxana Girju (14)
    Jana Diesner (15)

    14. Department of Linguistics and Beckman Institute     ; University of Illinois Urbana-Champaign ; Champaign ; USA
    15. Graduate School of Library and Information Science     ; University of Illinois Urbana-Champaign ; Champaign ; USA
  • 关键词：Uncertainty Automatic Analysis ; Supervised Sequence Labeling ; Unified Frameworks ; Morphologically ; Rich Languages ; Twitter
  • 刊名：Lecture Notes in Computer Science
  • 出版年：2015
  • 出版时间：2015
  • 年：2015
  • 卷：9041
  • 期：1
  • 页码：310-334
  • 全文大小：454 KB
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  • 作者单位：Computational Linguistics and Intelligent Text Processing
  • 丛书名：978-3-319-18110-3
  • 刊物类别：Computer Science
  • 刊物主题：Artificial Intelligence and Robotics
    Computer Communication Networks
    Software Engineering
    Data Encryption
    Database Management
    Computation by Abstract Devices
    Algorithm Analysis and Problem Complexity
  • 出版者：Springer Berlin / Heidelberg
  • ISSN：1611-3349
文摘
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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