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.
Q: The first model, referred as 'LSTM (PTB)' in the following sections, was trained on the sentences from Penn Treebank BIBREF12. The second model, referred as 'LSTM (FTB)', was trained on the sentences from French Treebank BIBREF13. We incorporate two pretrained English language models: one trained on the Billion Word benchmark (referred as 'LSTM (1B)') from BIBREF14, and the other trained on English Wikipedia (referred as 'LSTM (enWiki)') from BIBREF3. For French, we trained a large LSTM language model (referred as 'LSTM (frWaC)') on a random subset (about 4 million sentences, 138 million word tokens) of the frWaC dataset BIBREF15.
A:
What is the size of the datasets employed?