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: 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: In total around 500 different workers were involved in the annotation. about 500
Question: How many people participated in their evaluation study of table-to-text models?

SOLUTION: about 500

PROBLEM: To study how the multimodal context can boost the performance compared to an unimodal context we evaluate different models: a Feature Concatenation Model (FCM), a Spatial Concatenation Model (SCM) and a Textual Kernels Model (TKM)
Question: What models do they propose?

SOLUTION:
Feature Concatenation Model (FCM) Spatial Concatenation Model (SCM) Textual Kernels Model (TKM)