Miller, Tristan ; Sukhareva, Maria ; Gurevych, Iryna (2019)
A Streamlined Method for Sourcing Discourse-level Argumentation Annotations from the Crowd.
The 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019). Minneapolis, USA (02.10.2019-07.10.2019)
doi: 10.18653/v1/N19-1177
Konferenzveröffentlichung, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
The study of argumentation and the development of argument mining tools depends on the availability of annotated data, which is challenging to obtain in sufficient quantity and quality. We present a method that breaks down a popular but relatively complex discourse-level argument annotation scheme into a simpler, iterative procedure that can be applied even by untrained annotators. We apply this method in a crowdsourcing setup and report on the reliability of the annotations obtained. The source code for a tool implementing our annotation method, as well as the sample data we obtained (4909 gold-standard annotations across 982 documents), are freely released to the research community. These are intended to serve the needs of qualitative research into argumentation, as well as of data-driven approaches to argument mining.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Miller, Tristan ; Sukhareva, Maria ; Gurevych, Iryna |
| Art des Eintrags: | Bibliographie |
| Titel: | A Streamlined Method for Sourcing Discourse-level Argumentation Annotations from the Crowd |
| Sprache: | Englisch |
| Publikationsjahr: | 27 Februar 2019 |
| Ort: | Minneapolis, Minnesota |
| Verlag: | Association for Computational Linguistics |
| Buchtitel: | Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019) |
| Veranstaltungstitel: | The 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019) |
| Veranstaltungsort: | Minneapolis, USA |
| Veranstaltungsdatum: | 02.10.2019-07.10.2019 |
| DOI: | 10.18653/v1/N19-1177 |
| URL / URN: | https://aclanthology.org/N19-1177 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | The study of argumentation and the development of argument mining tools depends on the availability of annotated data, which is challenging to obtain in sufficient quantity and quality. We present a method that breaks down a popular but relatively complex discourse-level argument annotation scheme into a simpler, iterative procedure that can be applied even by untrained annotators. We apply this method in a crowdsourcing setup and report on the reliability of the annotations obtained. The source code for a tool implementing our annotation method, as well as the sample data we obtained (4909 gold-standard annotations across 982 documents), are freely released to the research community. These are intended to serve the needs of qualitative research into argumentation, as well as of data-driven approaches to argument mining. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen |
| Hinterlegungsdatum: | 18 Sep 2019 12:12 |
| Letzte Änderung: | 11 Jun 2024 07:11 |
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A Streamlined Method for Sourcing Discourse-level Argumentation Annotations from the Crowd. (deposited 27 Feb 2019 10:10)
- A Streamlined Method for Sourcing Discourse-level Argumentation Annotations from the Crowd. (deposited 18 Sep 2019 12:12) [Gegenwärtig angezeigt]
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