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We introduce a data set called DCH-2, which contains 4,390 realcustomer-helpdesk dialogues in Chinese and their English translations. DCH-2also contains dialogue-level annotations and turn-level annotations obtainedindependently from either 19 or 20 annotators. The data set was built throughour effort as organisers of the NTCIR-14 Short Text Conversation and NTCIR-15Dialogue Evaluation tasks, to help researchers understand what constitutes aneffective customer-helpdesk dialogue, and thereby build efficient and helpfulhelpdesk systems that are available to customers at all times. In addition,DCH-2 may be utilised for other purposes, for example, as a repository forretrieval-based dialogue systems, or as a parallel corpus for machinetranslation in the helpdesk domain.

DCH-2: A Parallel Customer-Helpdesk Dialogue Corpus with Distributions of Annotators' Labels