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.
--------
Question: The annotator carried out all annotation. 
 Question: How many annotators tagged each tweet?

Answer: One


Question: E2E NLG challenge Dataset: The training set of the E2E challenge dataset which consists of 42K samples was partitioned into a 10K paired and 32K unpaired datasets by a random process.  The Wikipedia Company Dataset: The Wikipedia company dataset presented in Section SECREF18 was filtered to contain only companies having abstracts of at least 7 words and at most 105 words. The dataset was then divided into: a training set (35K), a development set (4.3K) and a test set (4.3K). The training set was also partitioned in order to obtain the paired and unpaired datasets.  
 Question: What non-annotated datasets are considered?

Answer: E2E NLG challenge Dataset The Wikipedia Company Dataset


Question: The dataset at HASOC 2019 were given in three languages: Hindi, English, and German. Dataset in Hindi and English had three subtasks each, while German had only two subtasks. We participated in all the tasks provided by the organisers and decided to develop a single model that would be language agnostic. We used the same model architecture for all the three languages. The training dataset of Hindi dataset was more balanced than English or German dataset. Hence, the results were around 0.78. As the dataset in German language was highly imbalanced, the results drops to 0.62. 
 Question: What are the languages used to test the model?

Answer:
Hindi, English and German (German task won)


