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: The crowdworkers were located in the US and hired on the BIBREF22 platform.

Answer: Who are the crowdworkers?


Question: We map each relation type $R(x,y)$ to at least one parametrized natural-language question $q_x$ whose answer is $y$ .

Answer: How is the input triple translated to a slot-filling task?


Question: With the above hyperparameter setting, the hybrid NER model achieved a F1 score of $0.995$ on synthesized queries and $0.948$ on clinical notes while the i2b2 NER model achieved a F1 score of $0.441$ on synthesized queries and $0.927$ on clinical notes (See Table TABREF23).

Answer:
what were their performance results?