Identification of connected arguments based on reasoning schemes “from expert opinion”

N. V. Salomatina, I. S. Kononenko, E. A. Sidorova, I. S. Pimenov

Research output: Contribution to journalConference articlepeer-review

Abstract

The work presented describes a combined approach to the partial extraction of the argumentative structure of a text that can be employed in the absence of sufficient annotated data to apply efficiently the machine learning methods for the direct detection of arguments and their relations. In this case, argument identification is performed by using the patterns of argumentation indicators created by a linguist and automatically expanded. These patterns enable the recognition of specific argument types with fine precision. In this study, arguments “from expert opinion” serve as such a pivot type. Besides, potential relations between recognized arguments are analyzed by dividing the text into superphrasal units (fragments united by one topic). The criterion for connecting arguments in an argumentative structure is their inclusion in the same superphrasal unit. An experiment for identifying potentially related arguments is conducted on a set of popular science texts with a minimum size of 1000 words.

Original languageEnglish
Article number012013
JournalJournal of Physics: Conference Series
Volume1715
Issue number1
DOIs
Publication statusPublished - 4 Jan 2021
EventInternational Conference on Marchuk Scientific Readings 2020, MSR 2020 - Akademgorodok, Novosibirsk, Russian Federation
Duration: 19 Oct 202023 Oct 2020

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