EMNLP2020
doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset
Song Feng, Hui Wan, R. Chulaka Gunasekara, Siva Sankalp Patel, Sachindra Joshi, Luis A. Lastras
87 citations
Abstract
We introduce doc2dial, a new dataset of goal-oriented dialogues that are grounded in the associated documents. Inspired by how the authors compose documents for guiding end users, we first construct dialogue flows based on the content elements that corresponds to higher-level relations across text sections as well as lower-level relations between discourse units within a section. Then we present these dialogue flows to crowd contributors to create conversational utterances. The dataset includes over 4500 annotated conversations with an average of 14 turns that are grounded in over 450 documents from four domains. Compared to the prior document-grounded dialogue datasets, this dataset covers a variety of dialogue scenes in information-seeking conversations. For evaluating the versatility of the dataset, we introduce multiple dialogue modeling tasks and present baseline approaches. A9: Would you like to find out whether you are eligible? U10: That's exactly why I contact again! A11: Were there any damages to your clothes that were caused by prosthetic or orthopedic device or your skin medicine? U12: The latter happened.