instruction:
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.
question:
Then, it selects a subset of a 1,700-hour ( INLINEFORM2 1.1M instances) unlabeled dataset.
answer:
How much data samples do they start with before obtaining the initial model labels?


question:
Our main contributions are (1) the publication of Turkish corpus for coarse-grained and fine-grained NER, and TC research, (2) six different versions of corpus according to noise reduction methodology and entity types, (3) an analysis of the corpus and (4) benchmark comparisons for NER and TC tasks against human annotators. 
answer:
Did they experiment with the dataset on some tasks?


question:
For each variable in encoding set, learn the new embeddings using the embeddings train set . Since there is stochasticity in the embeddings training model, we will repeat the above multiple times, for the different experiments in the paper (and report the respective mean and standard deviation statistics).
answer:

How do their train their embeddings?