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 Q]: In the first one, shown in Figure FIGREF12, a special dedicated discriminator is added to the model to control that the latent representation does not contain stylistic information. The second extension of the baseline architecture does not use an adversarial component $D_z$ that is trying to eradicate information on $c$ from component $z$. Instead, the system, shown in Figure FIGREF16 feeds the "soft" generated sentence $\tilde{G}$ into encoder $E$ and checks how close is the representation $E(\tilde{G} )$ to the original representation $z = E(x)$ in terms of the cosine distance. We further refer to it as shifted autoencoder or SAE. We also study a combination of both approaches described above, shown on Figure FIGREF17. 
 Question: What are three new proposed architectures?
[EX A]: special dedicated discriminator is added to the model to control that the latent representation does not contain stylistic information shifted autoencoder or SAE combination of both approaches

[EX Q]: These workers completed 1001 tasks: 496 tasks in the control and 505 in the AUI.  
 Question: How many responses did they obtain?
[EX A]: 1001

[EX Q]: This corpus has multiple versions, and we choose the following two versions as their test dataset has significantly larger number of instances of multiple relation tuples with overlapping entities. (i) The first version is used by BIBREF6 (BIBREF6) (mentioned as NYT in their paper) and has 24 relations. We name this version as NYT24. (ii) The second version is used by BIBREF11 (BIBREF11) (mentioned as NYT10 in their paper) and has 29 relations. 
 Question: Are there datasets with relation tuples annotated, how big are datasets available?
[EX A]:
Yes