TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: While the dataset was collected with simulated environments, no structure was imposed on the navigation instructions while crowd-sourcing data. Thus, many instructions in our dataset are ambiguous. Moreover, the order of the behaviors in the instructions is not always the same. For instance, a person said "turn right and advance" to describe part of a route, while another person said "go straight after turning right" in a similar situation. The high variability present in the natural language descriptions of our dataset makes the problem of decoding instructions into behaviors not trivial. See Appendix A of the supplementary material for additional details on our data collection effort.

SOLUTION: What language is the experiment done in?

PROBLEM: Attention-base translation model We use the system of BIBREF6 , a convolutional sequence to sequence model.

SOLUTION: Which translation system do they use to translate to English?

PROBLEM: For the input, we build a parallel monolingual corpus by translating the mixed language sequence using Google NMT to English ( INLINEFORM0 ) and Mandarin ( INLINEFORM1 ) sequences.

SOLUTION:
What parallel corpus did they use?