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.
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Question: 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.

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

Question: Dataset Quality Analysis ::: Inter-Annotator Agreement (IAA)
To estimate dataset consistency across different annotations, we measure F1 using our UA metric with 5 generators per predicate. Dataset Quality Analysis ::: Dataset Assessment and Comparison
We assess both our gold standard set and the recent Dense set against an integrated expert annotated sample of 100 predicates. Dataset Quality Analysis ::: Agreement with PropBank Data
It is illuminating to observe the agreement between QA-SRL and PropBank (CoNLL-2009) annotations BIBREF7.

Answer: How was quality measured?

Question: We varied the number of experts between models, using ordinary MoE layers with 4, 32 and 256 experts and hierarchical MoE layers with 256, 1024 and 4096 experts.

Answer:
How is the correct number of experts to use decided?