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.

For instance, we observed that winter words were together and far away from summer ones. Week days were grouped as well and far from week-end days. 
 Question: What geometric properties do embeddings display?
Winter and summer words formed two separate clusters. Week day and week-end day words also formed separate clusters.

Since our methodology does not use a seed list of offensive words, it is not biased by topic, target, or dialect. Using our methodology, we tagged 10,000 Arabic tweet dataset for offensiveness, where offensive tweets account for roughly 19% of the tweets. Further, we labeled tweets as vulgar or hate speech. To date, this is the largest available dataset, which we plan to make publicly available along with annotation guidelines. We use this dataset to characterize Arabic offensive language to ascertain the topics, dialects, and users' gender that are most associated with the use of offensive language.  
 Question: In what way is the offensive dataset not biased by topic, dialect or target?
It does not use a seed list to gather tweets so the dataset does not skew to specific topics, dialect, targets.

We show the statistics of the dataset we use in tab:statistics, and the construction procedures will be introduced in this section. In Wikidata BIBREF8 , facts can be described as (Head item/property, Property, Tail item/property).  We first choose the most common 202 relations and 120000 entities from Wikidata as our initial data. ReVerb BIBREF9 is a program that automatically identifies and extracts binary relationships from English sentences. We use the extractions from running ReVerb on Wikipedia. FB15K BIBREF3 is a subset of freebase. TACRED BIBREF10 is a large supervised relation extraction dataset obtained via crowdsourcing. We directly use these two dataset, no extra processing steps were applied. 
 Question: Which knowledge bases do they use?

Wikidata ReVerb FB15K TACRED