In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Input: Consider Input: We develop a null model to determine how much variation in binomial orderings we might expect across communities and across time, if binomial orderings were randomly ordered according to global asymmetry values.
Question: What new model is proposed for binomial lists?

Output: null model

Input: Consider Input: The Y-axis in the figure is the success rate of the agent (measured in terms of number of dialogs that resulted in launching a skill divided by total number of dialogs), and the X-axis is the number of learning steps.
Question: How did they measure effectiveness?

Output: number of dialogs that resulted in launching a skill divided by total number of dialogs

Input: Consider Input: When we include the LM embeddings in our system overall performance increases from 90.87% to 91.93% INLINEFORM0 for the CoNLL 2003 NER task, a more then 1% absolute F1 increase, and a substantial improvement over the previous state of the art. We also establish a new state of the art result (96.37% INLINEFORM1 ) for the CoNLL 2000 Chunking task.
Question: what results do they achieve?
Output: 91.93% F1 score on CoNLL 2003 NER task and 96.37% F1 score on CoNLL 2000 Chunking task