TASK DEFINITION: In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.
PROBLEM: The observed performance of both the BasicDCGAN and MultitaskDCGAN using 3-classes is comparable to the state-of-the-art, with 49.80% compared to 49.99% reported in BIBREF16  
 Question: What model achieves state of the art performance on this task?

SOLUTION: BIBREF16

PROBLEM: For English dataset, we crawl 687 cybersecurity articles from a collection of advanced persistent threats (APT) reports which are published from 2008 to 2018.  
 Question: Where are the cybersecurity articles used in the model sourced from?

SOLUTION:  from a collection of advanced persistent threats (APT) reports which are published from 2008 to 2018

PROBLEM: 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. 
 Question: How much labeled data is available for these two languages?

SOLUTION:
10k training and 1k test 1,101 sentences (26k tokens)