An Online Annotation Assistant for Argument Schemes
Understanding the inferential principles underpinning an argument is essential to the proper interpretation and evaluation of persuasive discourse. Argument schemes capture the conventional patterns of reasoning appealed to in persuasion. The empirical study of these patterns relies on the availability of data about the actual use of argumentation in communicative practice. Annotated corpora of argument schemes, however, are scarce, small, and unrepresentative. Aiming to address this issue, we present one step in the development of improved datasets by integrating the Argument Scheme Key {--} a novel annotation method based on one of the most popular typologies of argument schemes {--} into the widely used OVA software for argument analysis.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Proposed Method for Annotation of Scientific Arguments in Terms of Semantic Relations and Argument Schemes
This paper presents a proposed method for annotation of scientific arguments in biological/biomedical journal articles. Semantic entities and relations are used to represent the propositional content of arguments in inst…
Argument MiningArticlesTowards Assessing Argumentation Annotation - A First Step
This paper presents a first attempt at using Walton{'}s argumentation schemes for annotating arguments in Swedish political text and assessing the feasibility of using this particular set of schemes with two linguistical…
Semantically Constrained Multilayer Annotation: The Case of Coreference
We propose a coreference annotation scheme as a layer on top of the Universal Conceptual Cognitive Annotation foundational layer, treating units in predicate-argument structure as a basis for entity and event mentions. W…
Annotating Claims in the Vaccination Debate
In this paper we present annotation experiments with three different annotation schemes for the identification of argument components in texts related to the vaccination debate. Identifying claims about vaccinations made…
Argument Mining