Revisiting Computational Models of Argument Schemes: Classification, Annotation, Comparison

被引:10
|
作者
Visser, Jacky [1 ]
Lawrence, John [1 ]
Wagemans, Jean [2 ]
Reed, Chris [1 ]
机构
[1] Univ Dundee, Ctr Argument Technol, Dundee, Scotland
[2] Univ Amsterdam, Argumentat & Rhetor, Amsterdam, Netherlands
基金
英国工程与自然科学研究理事会;
关键词
annotation; argument mining; argument schemes; classification; corpus;
D O I
10.3233/978-1-61499-906-5-313
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present an in-depth comparative analysis of two classifications of argument schemes: Walton's typology and Wagemans' Periodic Table of Arguments. We describe annotation guidelines for each classification and apply these to a corpus of arguments from the 2016 US presidential debates. In so doing, we achieve substantial inter-annotator agreement, and produce what, to the best of our knowledge, are the two largest and most reliably annotated corpora of argument schemes in dialogical argumentation publicly available. In describing the creation and comparison of these corpora, we discuss the strengths of each, with an eye towards both computational modelling and argument mining.
引用
收藏
页码:313 / 324
页数:12
相关论文
共 50 条
  • [1] An Online Annotation Assistant for Argument Schemes
    Lawrence, John
    Visser, Jacky
    Reed, Chris
    [J]. 13TH LINGUISTIC ANNOTATION WORKSHOP (LAW XIII), 2019, : 100 - 107
  • [2] Comparison of functional annotation schemes for genomes
    Rison S.C.G.
    Hodgman T.C.
    Thornton J.M.
    [J]. Functional & Integrative Genomics, 2000, 1 (1) : 56 - 69
  • [3] Computational schemes for the prediction and annotation of enhancers from epigenomic assays
    Whitaker, John W.
    Nguyen, Tung T.
    Zhu, Yun
    Wildberg, Andre
    Wang, Wei
    [J]. METHODS, 2015, 72 : 86 - 94
  • [4] Gaussian process classification: singly versus doubly stochastic models, and new computational schemes
    Jens Röder
    Raimon Tolosana-Delgado
    Fred A. Hamprecht
    [J]. Stochastic Environmental Research and Risk Assessment, 2011, 25
  • [5] Gaussian process classification: singly versus doubly stochastic models, and new computational schemes
    Roeder, Jens
    Tolosana-Delgado, Raimon
    Hamprecht, Fred A.
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2011, 25 (07) : 865 - 879
  • [6] Recent advances in computational models of natural argument
    Reed, Chris
    Grasso, Floriana
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2007, 22 (01) : 1 - 15
  • [7] Special issue: Computational models of natural argument
    Grasso, Floriana
    Bex, Floris
    Green, Nancy
    [J]. ARGUMENT & COMPUTATION, 2016, 7 (01) : 3 - +
  • [8] A COMPARISON OF TURBULENCE CLASSIFICATION SCHEMES
    SEDEFIAN, L
    BENNETT, E
    [J]. ATMOSPHERIC ENVIRONMENT, 1980, 14 (07) : 741 - 750
  • [9] COMPARISON OF CLASSIFICATION SCHEMES FOR LIBRARIES
    BURY, S
    [J]. LIBRARY SCIENCE WITH A SLANT TO DOCUMENTATION, 1980, 17 (03): : 73 - 82
  • [10] Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes
    Sabo, Ofer
    Elazar, Yanai
    Goldberg, Yoav
    Dagan, Ido
    [J]. TRANSACTIONS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, 2021, 9 : 691 - 706