New York City Lights Scenic Bridge View Concept

Frames Dataset

Summary

1,369

Dialogues

Average number of turns per dialogue

268

Hotels

109

Cities

4.58

Average user satisfaction (from 1-5)

19,986

Turns

Data Analysis

User and Machine Actions

Here, we provide some insight into the annotation scheme: each frame is given an id (here, 1 and 2). When values from one frame are used in another frame, we use a ref tag to point to the reference frame.

User	I’d like to book a trip to boston from London on Saturday, August 13, 2016 for 8 adults. I have a tight budget of 1700.	Frame #1
Act 1	inform(intent=book)
Act 2	inform(dst_city = boston, or_city = London, str_date = Saturday\, August 13\, 2016, n_adults = 8, budget = 1700)”
Wizard	“Hi…I checked a few options for you, and unfortunately, we do not currently have any trips that meet this criteria. Would you like to book an alternate travel option?”	Frame #1
Act 1	no_result
Act 2	suggest(dst_city)
User	“Yes, how about going to Detroit from London on August 13, 2016 for 5 adults. For this trip, my budget would be 1900.”	Frame #2
Act 1	inform(dst_city = Detroit, n_adults = 5, budget = 1900, ref = [1{or_city = London, str = August 13\, 2016}])
Wizard	“I checked the availability for those dates and there were no trips available. Would you like to select some alternate dates?”	Frame #2
Act 1	no_result(str_date, end_date)
Act 2	suggest(str_date, end_date)