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:
 In terms of this, rather than starting from Twitter API Search, we look into the archived snapshots of two major news websites (CNN, NBC), and then extract the tweet blocks that are embedded in the news articles.
answer:
How do they determine if tweets have been used by journalists?


question:
We manually reviewed 1,177 pairs of entities and referring expressions generated by the system. Overall, 73.3% of the non-first mentions of entities were replaced with suitable shorter and more fluent expressions.
answer:
How is fluency of generated text evaluated?


question:
We use the Universal Dependencies' Hindi-English codemixed data set BIBREF9 to test the model's ability to label code-mixed data. This dataset is based on code-switching tweets of Hindi and English multilingual speakers. We use the Devanagari script provided by the data set as input tokens.
answer:

What codemixed language pairs are evaluated?