"Sharks are not the threat humans are": Argument Component Segmentation
in School Student Essays
- URL: http://arxiv.org/abs/2103.04518v1
- Date: Mon, 8 Mar 2021 02:40:07 GMT
- Title: "Sharks are not the threat humans are": Argument Component Segmentation
in School Student Essays
- Authors: Tariq Alhindi and Debanjan Ghosh
- Abstract summary: We apply a token-level classification to identify claim and premise tokens from a new corpus of argumentative essays written by middle school students.
We demonstrate that a BERT-based multi-task learning architecture (i.e., token and sentence level classification) adaptively pretrained on a relevant unlabeled dataset obtains the best results.
- Score: 3.632177840361928
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Argument mining is often addressed by a pipeline method where segmentation of
text into argumentative units is conducted first and proceeded by an argument
component identification task. In this research, we apply a token-level
classification to identify claim and premise tokens from a new corpus of
argumentative essays written by middle school students. To this end, we compare
a variety of state-of-the-art models such as discrete features and deep
learning architectures (e.g., BiLSTM networks and BERT-based architectures) to
identify the argument components. We demonstrate that a BERT-based multi-task
learning architecture (i.e., token and sentence level classification)
adaptively pretrained on a relevant unlabeled dataset obtains the best results
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