Approach to Building a Dataset for the Problem of Extracting Argumentative Relations.

Autor: Sidorova, E. A., Zagorulko, Yu. A., Kononenko, I. S., Sery, A. S., Chagina, P. M.
Zdroj: Pattern Recognition & Image Analysis; Sep2024, Vol. 34 Issue 3, p515-522, 8p
Abstrakt: The paper addresses data generation methods for training neural network models and solving problems of argument mining. Data preparation includes the creation of an annotated corpus and the generation of a dataset for a specific task and the selected training model. Corpora annotated manually by experts can be augmented with synthetic text data derived from paraphrasing or back-translating the texts of the base corpus. A specific feature of the task of generating a dataset is the need to identify components in the text and indicate their role in the argument (premise, thesis, counterargument). The role of argumentation indicators in the problem of data preparation is discussed and a statistical study of the information content of indicators on the prepared ArgNet corpus is carried out. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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