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]: For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two different domains For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two different domains The evaluation of the German version is in progress.
[EX A]: What are the corpora used for the task?

[EX Q]: The annotation projection method, which we follow in this work, is one way to address this problem. It was introduced for POS tagging, base noun phrase bracketing, NER tagging, and inflectional morphological analysis BIBREF29 but it has also been used for dependency parsing BIBREF30 , role labeling BIBREF31 , BIBREF32 and semantic parsing BIBREF26 .
[EX A]: Do the authors test their annotation projection techniques on tasks other than AMR?

[EX Q]: We presented a new approach for converting between masculine-inflected and feminine-inflected noun phrases in morphologically rich languages. To do this, we introduced a Markov random field with an optional neural parameterization that infers the manner in which a sentence must change to preserve morpho-syntactic agreement when altering the grammatical gender of particular nouns.
[EX A]:
Which model do they use to convert between masculine-inflected and feminine-inflected sentences?