Detailed Instructions: 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.
See one example below:
Problem: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequence model. Large-Scale Chinese Short Text Summarization Dataset (LCSTS) is constructed by BIBREF1 . The dataset consists of more than 2.4 million text-summary pairs in total, constructed from a famous Chinese social media microblogging service Weibo.
Question: Are results reported only for English data?
Solution: No
Explanation: Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.

Problem: Fortunately, 180221 of 231162 author names could be matched successfully. There are many reasons for the remaining uncovered cases. 9073 Latin names could not be found in the name dictionary ENAMDICT and 14827 name matchings between the names' Latin and kanji representations did not succeed. These names might be missing at all in the dictionary, delivered in a very unusual format that the tool does not cover, or might not be Japanese or human names at all. Of course, Japanese computer scientists sometimes also cooperate with foreign colleagues but our tool expects Japanese names and is optimized for them.
Question: How successful are they at matching names of authors in Japanese and English?
Solution:
180221 of 231162 author names could be matched successfully