Table 3.

Main available datasets for conversational agents—part A.

General-Purpose Datasets
Dataset	Source	Description	Size	Used for
DailyDialog [213]	hand written,	daily interactions	13,118 dialogs,	general
	manualy labeled		$\tilde{7}$.9 turns	purpose
[216]	subtitles	interaction–response		purpose
		pairs
Movie dialogue dataset	movie metadata	OMDb, MovieLens,	3.1 M simulated	Movies QA and
[217]	as knowledge triples	and Reddit	QA pairs	recommendation
Cornell Movie Dialogues	Short conversations	movie metadata	220 K	understanding
Corpus [218]	from film scripts		conversations	linguistic style
Ubuntu dialogue	Ubuntu chat stream	human–human chat	930 K	response
corpus [224]			conversations	generation
Question-Answering Datasets
Squad Version 1.1	questions and answers	$\tilde{1}$00 K questions	100 K q&a	machine reading
[227]	on Wikipedia articles	on Wikipedia articles		comprehension
Squad Version 2	questions and answers	Squad 1.1 +	100 K Q&A +	machine reading
[228]	and additional questions	50 k questions	50 k questions	comprehension
	with no answers	with no answers
CNN/Daily Mail	queries from the CNN	cont.–query–answer	$\tilde{1}$M stories+	machine reading
comprehension [229]	and Daily Mail websites	triples	associated queries	training dataset
Natural Questions	Google search queries+	Google question+	307,372	training &
dataset [230]	Wikipedia answers	long answer+	training examples	evaluation of
	by crowd workers	short answers		answ. systems
TriviaQA	crowdworkers	question-answer-	95 K quest.-ans.	reading
[231]	questions	evidence triples	pairs + 6 evidence	comprehension
			doc. per quest.