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.

[Q]: To account for sequences of words and characters that might carry useful information, we extracted word unigrams, bigrams, and trigrams as features. 
 Question: Which features do they use to model Twitter messages?
[A]: word unigrams, bigrams, and trigrams


[Q]: In its general form, a type-logical grammar consists of following components: 
 Question: Does Grail accept Prolog inputs?
[A]: No


[Q]: When predicting anger, joy, or valence, the number of systems consistently giving higher scores to sentences with female noun phrases (21–25) is markedly higher than the number of systems giving higher scores to sentences with male noun phrases (8–13). (Recall that higher valence means more positive sentiment.) In contrast, on the fear task, most submissions tended to assign higher scores to sentences with male noun phrases (23) as compared to the number of systems giving higher scores to sentences with female noun phrases (12). When predicting sadness, the number of submissions that mostly assigned higher scores to sentences with female noun phrases (18) is close to the number of submissions that mostly assigned higher scores to sentences with male noun phrases (16). These results are in line with some common stereotypes, such as females are more emotional, and situations involving male agents are more fearful BIBREF27  The majority of the systems assigned higher scores to sentences with African American names on the tasks of anger, fear, and sadness intensity prediction. On the joy and valence tasks, most submissions tended to assign higher scores to sentences with European American names. These tendencies reflect some common stereotypes that associate African Americans with more negative emotions BIBREF28 . 
 Question: Which race and gender are given higher sentiment intensity predictions?
[A]:
Females are given higher sentiment intensity when predicting anger, joy or valence, but males are given higher sentiment intensity when predicting  fear.
African American names are given higher score on the tasks of anger, fear, and sadness intensity prediction,  but European American names are given higher scores on joy and valence task.