Projects per year
Abstract
We introduce a corpus of the 2016 U.S. presidential debates and commentary, containing 4,648 argumentative propositions annotated with fine-grained proposition types. Modern machine learning pipelines for analyzing argument have difficulty distinguishing between types of propositions based on their factuality, rhetorical positioning, and speaker commitment. Inability to properly account for these facets leaves such systems inaccurate in understanding of fine-grained proposition types. In this paper, we demonstrate an approach to annotating for four complex proposition types, namely normative claims, desires, future possibility, and reported speech. We develop a hybrid machine learning and human workflow for annotation that allows for efficient and reliable annotation of complex linguistic phenomena, and demonstrate with preliminary analysis of rhetorical strategies and structure in presidential debates. This new dataset and method can support technical researchers seeking more nuanced representations of argument, as well as argumentation theorists developing new quantitative analyses.
Original language | English |
---|---|
Title of host publication | Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) |
Editors | Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis |
Publisher | European Language Resources Association (ELRA) |
Pages | 1008-1018 |
Number of pages | 11 |
ISBN (Electronic) | 9791095546344 |
Publication status | Published - 2020 |
Event | 12th International Conference on Language Resources and Evaluation, LREC 2020 - Marseille, France Duration: 11 May 2020 → 16 May 2020 |
Conference
Conference | 12th International Conference on Language Resources and Evaluation, LREC 2020 |
---|---|
Country/Territory | France |
City | Marseille |
Period | 11/05/20 → 16/05/20 |
Keywords
- Argumentation theory
- Hybrid annotation systems
- Imbalanced annotation tasks
- Proposition types
ASJC Scopus subject areas
- Language and Linguistics
- Education
- Library and Information Sciences
- Linguistics and Language
Fingerprint
Dive into the research topics of 'Machine-aided annotation for fine-grained proposition types in argumentation'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Argument Mining
Engineering and Physical Sciences Research Council
1/01/16 → 31/12/19
Project: Research