2019 ACL ACL 2019

Annotation of Rhetorical Moves in Biochemistry Articles

Abstract

AbstractThis paper focuses on the real world application of scientific writing and on determining rhetorical moves, an important step in establishing the argument structure of biomedical articles. Using the observation that the structure of scholarly writing in laboratory-based experimental sciences closely follows laboratory procedures, we examine most closely the Methods section of the texts and adopt an approach of identifying rhetorical moves that are procedure-oriented. We also propose a verb-centric frame semantics with an effective set of semantic roles in order to support the analysis. These components are designed to support a computational model that extends a promising proposal of appropriate rhetorical moves for this domain, but one which is merely descriptive. Our work also contributes to the understanding of argument-related annotation schemes. In particular, we conduct a detailed study with human annotators to confirm that our selection of semantic roles is effective in determining the underlying rhetorical structure of existing biomedical articles in an extensive dataset. The annotated dataset that we produce provides the important knowledge needed for our ultimate goal of analyzing biochemistry articles.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Healthcare & Medicine and Knowledge & Reasoning and Natural Language Processing
🧭 Keyword Pioneer — rhetorical move
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics