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.
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Question: We use the Dialogue State Tracking Competition 2 (DSTC2) dataset BIBREF27 which is the most widely used dataset for research on task-oriented chatbots.  We also used two other datasets recently open-sourced by Google Research BIBREF28 which are M2M-sim-M (dataset in movie domain) and M2M-sim-R (dataset in restaurant domain). 

Answer: What are the three datasets used?


Question: The Hausa data used in this paper is part of the LORELEI language pack. It consists of Broad Operational Language Translation (BOLT) data gathered from news sites, forums, weblogs, Wikipedia articles and twitter messages. We use a split of 10k training and 1k test instances. The Yorùbá NER data used in this work is the annotated corpus of Global Voices news articles recently released by BIBREF22. The dataset consists of 1,101 sentences (26k tokens) divided into 709 training sentences, 113 validation sentences and 279 test sentences based on 65%/10%/25% split ratio.

Answer: How much labeled data is available for these two languages?


Question: Therefore, we decided to compile our own corpora based on English documents, which we crawled from different publicly accessible sources.

Answer:
Do they report results only on English data?


