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.

[EX Q]: Our model yields the best results on both UAS and LAS metrics of all languages except the Japanese. As for Japanese, our model gives unsatisfactory results because the original treebank was written in Roman phonetic characters instead of hiragana, which is used by both common Japanese writing and our pre-trained embeddings. Despite this, our model overall still gives 1.0% higher average UAS and LAS than the previous best parser, BIAF. Although both BIAF and STACKPTR parsers have achieved relatively high parsing accuracies on the 12 languages and have all UAS higher than 90%, our model achieves state-of-the-art results in all languages for both UAS and LAS. Overall, our model reports more than 1.0% higher average UAS than STACKPTR and 0.3% higher than BIAF.
[EX A]: What are performance compared to former models?

[EX Q]: Both systems were optimized on the tst2014 using Minimum error rate training BIBREF20 . A detailed description of the systems can be found in BIBREF21 .
[EX A]: How is the PBMT system trained?

[EX Q]: Cuneiform is an ancient writing system invented by the Sumerians for more than three millennia.
[EX A]:
What is one of the first writing systems in the world?