A Computational Analysis of Vagueness in Revisions of Instructional Texts
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Abstract (arXiv)
WikiHow is an open-domain repository of instructional articles for a variety of tasks, which can be revised by users. In this paper, we extract pairwise versions of an instruction before and after a revision was made. Starting from a noisy dataset of revision histories, we specifically extract and analyze edits that involve cases of vagueness in instructions. We further investigate the ability of a neural model to distinguish between two versions of an instruction in our data by adopting a pairwise ranking task from previous work and showing improvements over existing baselines.
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References · 8
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 723
- 2018Learning Word Vectors for 157 Languagescited by 280
- 2019Encode, Tag, Realize: High-Precision Text Editingcited by 99
- 2016Improving Hypernymy Detection with an Integrated Path-based and Distributional Methodcited by 27
- 2018Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corporacited by 26
- 2018Automatic Detection of Vague Words and Sentences in Privacy Policiescited by 10
- 2017The NLTK FrameNet API: Designing for Discoverability with a Rich Linguistic Resourcecited by 2
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