Year: 2023
Type: conference-paper
Abstract: Automated text simplification, a technique useful for making text more accessible to people such as children and emergent bilinguals, is often thought of as a monolingual translation task from complex to simplified text.This view fails to account for elaborative simplification, where new information is added into the simplified text.This paper proposes to view elaborative simplification through the lens of the Question Under Discussion (QUD) framework, providing a robust way to investigate what writers elaborate upon, how they elaborate, and how elaborations fit into the discourse context by viewing elaborations as explicit answers to implicit questions.We introduce ELABQUD, consisting of 1.3K elaborations accompanied with implicit QUDs, to study these phenomena.We show that explicitly modeling QUD (via question generation) not only provides essential understanding of elaborative simplification and how the elaborations connect with the rest of the discourse, but also substantially improves the quality of elaboration generation.
Authors: Yating Wu, William Sheffield, Kyle Mahowald, Junyi Li
Institution: The University of Texas at Austin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4389524461