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 target data, the code is written in Python programming language. 
 Question: What programming language is target language?

SOLUTION: Python

PROBLEM: As in the Sequicity framework, we report entity match rate, BLEU score and Success F1 score.  
 Question: What were the evaluation metrics used?

SOLUTION: entity match rate BLEU score Success F1 score

PROBLEM: Thus we propose two kinds of relation-specific meta information: relation meta and gradient meta corresponding to afore mentioned two perspectives respectively. In our proposed framework MetaR, relation meta is the high-order representation of a relation connecting head and tail entities. Gradient meta is the loss gradient of relation meta which will be used to make a rapid update before transferring relation meta to incomplete triples during prediction. 
 Question: What meta-information is being transferred?

SOLUTION:
high-order representation of a relation, loss gradient of relation meta