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.

Input: Consider Input: The current state-of-the-art approach BIBREF14 , BIBREF15 uses maximum entropy and CRF models with a combination of language model and hand-crafted features to predict if each character in the hashtag is the beginning of a new word.

Output: What current state of the art method was used for comparison?

Input: Consider Input: Our official scores (column Ens Test in Table TABREF19 ) have placed us second (EI-Reg, EI-Oc), fourth (V-Reg) and fifth (V-Oc) on the SemEval AIT-2018 leaderboard.

Output: What were the scores of their system?

Input: Consider Input: To deal with negative values, we propose clipped $\mathit {PMI}$,

which is equivalent to $\mathit {PPMI}$ when $z = 0$. In practice we find this works poorly if done symmetrically, so we introduce a variant called $\mathit {NNEGPMI}$ which only normalizes $\mathit { exttt {-}PMI}$:
Output: What novel PMI variants are introduced?