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: Attention-base translation model We use the system of BIBREF6 , a convolutional sequence to sequence model. 
 Question: Which translation system do they use to translate to English?

SOLUTION: Attention-based translation model with convolution sequence to sequence model

PROBLEM: In Table TABREF26 we report the results of our model on the three datasets standardly used for the evaluation of emotion classification, which we have described in Section SECREF3 . 
 Question: What was their performance on emotion detection?

SOLUTION: Answer with content missing: (Table 3) Best author's model B-M average micro f-score is 0.409, 0.459, 0.411 on Affective, Fairy Tales and ISEAR datasets respectively. 

PROBLEM: We used the following affective resources relying on different emotion models.

Emolex: it contains 14,182 words associated with eight primary emotion based on the Plutchik model BIBREF10 , BIBREF11 .

EmoSenticNet(EmoSN): it is an enriched version of SenticNet BIBREF12 including 13,189 words labeled by six Ekman's basic emotion BIBREF13 , BIBREF14 .

Dictionary of Affect in Language (DAL): includes 8,742 English words labeled by three scores representing three dimensions: Pleasantness, Activation and Imagery BIBREF15 .

Affective Norms for English Words (ANEW): consists of 1,034 English words BIBREF16 rated with ratings based on the Valence-Arousal-Dominance (VAD) model BIBREF17 .

Linguistic Inquiry and Word Count (LIWC): this psycholinguistic resource BIBREF18 includes 4,500 words distributed into 64 emotional categories including positive (PosEMO) and negative (NegEMO). 
 Question: What affective-based features are used?

SOLUTION:
affective features provided by different emotion models such as Emolex, EmoSenticNet, Dictionary of Affect in Language, Affective Norms for English Words and Linguistics Inquiry and Word Count