TASK DEFINITION: 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.
PROBLEM: Our submissions ranked second (EI-Reg), second (EI-Oc), fourth (V-Reg) and fifth (V-Oc), demonstrating that the proposed method is accurate in automatically determining the intensity of emotions and sentiment of Spanish tweets. 
 Question: What subtasks did they participate in?

SOLUTION: Answer with content missing: (Subscript 1: "We did not participate in subtask 5 (E-c)") Authors participated in EI-Reg, EI-Oc, V-Reg and V-Oc subtasks.

PROBLEM:  Models include both neural nets (e.g. RNNs, CNNs) and standard machine learning tools (e.g. Naive Bayes with Laplace Smoothing, k-clustering, SVM with linear kernel).  
 Question: Which machine learning models are used?

SOLUTION: RNNs CNNs Naive Bayes with Laplace Smoothing k-clustering SVM with linear kernel

PROBLEM: Our ASR and ST models follow the architecture in berard2018end, but have 3 decoder layers like that in pino2019harnessing. 
 Question: What is the architecture of their model?

SOLUTION:
follow the architecture in berard2018end, but have 3 decoder layers like that in pino2019harnessing