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.

Ex Input:
The second data batch consists of event-related tweets for five natural disasters occurring in the U.S. in 2018. These are: the East Coast Bomb Cyclone (Jan. 2 - 6); the Mendocino, California wildfires (Jul. 27 - Sept. 18); Hurricane Florence (Aug. 31 - Sept. 19); Hurricane Michael (Oct. 7 - 16); and the California Camp Fires (Nov. 8 - 25).
Question: Which five natural disasters were examined?

Ex Output:
the East Coast Bomb Cyclone the Mendocino, California wildfires Hurricane Florence Hurricane Michael the California Camp Fires

Ex Input:
In order to derive the discourse features, an entity grid is constructed by feeding the document through an NLP pipeline to identify salient entities. Two flavors of discourse features are created by populating the entity grid with either (i) grammatical relations (GR) or (ii) RST discourse relations (RST).
Question: What discourse features are used?

Ex Output:
Entity grid with grammatical relations and RST discourse relations.

Ex Input:
We compare our best F1 score with other state-of-the-art approaches in table TABREF39 , which shows our model has competitive advantage in dealing with drug-drug interaction extraction.
Question: What is the performance of their model?

Ex Output:
Answer with content missing: (Table II) Proposed model has F1 score of 0.7220.