16/11/2020

doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset

Song Feng, Hui Wan, Chulaka Gunasekara, Siva Patel, Sachindra Joshi, Luis Lastras

Keywords: information-seeking conversations, dialogue tasks, dialogue flows, content elements

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.

 0
 0
 0
 0
This is an embedded video. Talk and the respective paper are published at EMNLP 2020 virtual conference. If you are one of the authors of the paper and want to manage your upload, see the question "My papertalk has been externally embedded..." in the FAQ section.

Comments

Post Comment
no comments yet
code of conduct: tbd

Similar Papers