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: To report the result for answer selection, MAP and MRR are used; however, the answer triggering task is evaluated by F1-score. The result for MULT Method is reported in Table. 1.

Output: Is accuracy the only metric they used to compare systems?


Input: Consider Input: GPT-2 achieves the highest score and the $n$-gram the lowest. Transformer-XL and the LSTM LM perform in the middle, and at roughly the same level as each other. We report the 12-category accuracy results for all models and human evaluation in Table TABREF14.

Output: What is the performance of the models on the tasks?


Input: Consider Input: The BD-4SK-ASR Dataset ::: The Language Model
We created the language from the transcriptions. The model was created using CMUSphinx in which (fixed) discount mass is 0.5, and backoffs are computed using the ratio method. The model includes 283 unigrams, 5337 bigrams, and 6935 trigrams.


Output: What are the results of the experiment?