Annotating very large arguments

Kamila Gorska; Wassiliki Siskou; Chris Reed

doi:10.3233/FAIA220171

Annotating very large arguments

Kamila Gorska (Lead / Corresponding author)
, Wassiliki Siskou
, Chris Reed

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

129 Downloads (Pure)

Abstract

We present a method of annotating very large arguments, with the use of IMC-Tool. IMC-Tool aids in creating long-distance argument structure relations, by providing a simple annotation tool, and integration software to synthesise argument annotations at scale.

Original language	English
Title of host publication	Computational Models of Argument
Subtitle of host publication	Proceedings of COMMA 2022
Editors	Francesca Toni, Sylwia Polberg, Richard Booth, Martin Caminada, Hiroyuki Kido
Publisher	IOS Press BV
Pages	357-358
Number of pages	2
ISBN (Electronic)	978-1-64368-307-2
ISBN (Print)	978-1-64368-306-5
DOIs	https://doi.org/10.3233/FAIA220171
Publication status	Published - 7 Sept 2022
Event	9th International Conference on Computational Models of Argument 2022 - Cardiff University, Cardiff, United Kingdom Duration: 14 Sept 2022 → 16 Sept 2022 https://comma22.cs.cf.ac.uk/

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	978-1-64368-307-2
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

Conference

Conference	9th International Conference on Computational Models of Argument 2022
Abbreviated title	COMMA 2022
Country/Territory	United Kingdom
City	Cardiff
Period	14/09/22 → 16/09/22
Internet address	https://comma22.cs.cf.ac.uk/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

argument annotation
inter-map correspondence
large arguments

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.3233/FAIA220171Licence: CC BY-NC

FAIA-353-FAIA220171Final published version, 284 KBLicence: CC BY-NC

Cite this

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title = "Annotating very large arguments",

abstract = "We present a method of annotating very large arguments, with the use of IMC-Tool. IMC-Tool aids in creating long-distance argument structure relations, by providing a simple annotation tool, and integration software to synthesise argument annotations at scale.",

keywords = "argument annotation, inter-map correspondence, large arguments",

author = "Kamila Gorska and Wassiliki Siskou and Chris Reed",

note = "Publisher Copyright: {\textcopyright} 2022 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).; 9th International Conference on Computational Models of Argument 2022, COMMA 2022 ; Conference date: 14-09-2022 Through 16-09-2022",

year = "2022",

month = sep,

day = "7",

doi = "10.3233/FAIA220171",

language = "English",

isbn = "978-1-64368-306-5",

series = "Frontiers in Artificial Intelligence and Applications",

publisher = "IOS Press BV",

pages = "357--358",

editor = "Francesca Toni and Sylwia Polberg and Richard Booth and Martin Caminada and Hiroyuki Kido",

booktitle = "Computational Models of Argument",

url = "https://comma22.cs.cf.ac.uk/",

}

Gorska, K, Siskou, W & Reed, C 2022, Annotating very large arguments. in F Toni, S Polberg, R Booth, M Caminada & H Kido (eds), Computational Models of Argument: Proceedings of COMMA 2022. Frontiers in Artificial Intelligence and Applications, vol. 978-1-64368-307-2, IOS Press BV, pp. 357-358, 9th International Conference on Computational Models of Argument 2022, Cardiff, United Kingdom, 14/09/22. https://doi.org/10.3233/FAIA220171

Annotating very large arguments. / Gorska, Kamila (Lead / Corresponding author); Siskou, Wassiliki; Reed, Chris.
Computational Models of Argument: Proceedings of COMMA 2022. ed. / Francesca Toni; Sylwia Polberg; Richard Booth; Martin Caminada; Hiroyuki Kido. IOS Press BV, 2022. p. 357-358 (Frontiers in Artificial Intelligence and Applications; Vol. 978-1-64368-307-2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Annotating very large arguments

AU - Gorska, Kamila

AU - Siskou, Wassiliki

AU - Reed, Chris

N1 - Publisher Copyright: © 2022 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).

PY - 2022/9/7

Y1 - 2022/9/7

N2 - We present a method of annotating very large arguments, with the use of IMC-Tool. IMC-Tool aids in creating long-distance argument structure relations, by providing a simple annotation tool, and integration software to synthesise argument annotations at scale.

AB - We present a method of annotating very large arguments, with the use of IMC-Tool. IMC-Tool aids in creating long-distance argument structure relations, by providing a simple annotation tool, and integration software to synthesise argument annotations at scale.

KW - argument annotation

KW - inter-map correspondence

KW - large arguments

UR - https://www.scopus.com/pages/publications/85139500509

UR - https://comma22.cs.cf.ac.uk/

U2 - 10.3233/FAIA220171

DO - 10.3233/FAIA220171

M3 - Conference contribution

AN - SCOPUS:85139500509

SN - 978-1-64368-306-5

T3 - Frontiers in Artificial Intelligence and Applications

SP - 357

EP - 358

BT - Computational Models of Argument

A2 - Toni, Francesca

A2 - Polberg, Sylwia

A2 - Booth, Richard

A2 - Caminada, Martin

A2 - Kido, Hiroyuki

PB - IOS Press BV

T2 - 9th International Conference on Computational Models of Argument 2022

Y2 - 14 September 2022 through 16 September 2022

ER -

Annotating very large arguments

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this