Given the task definition, example input & output, solve the new input case.
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.
Example: 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?
Output: No
Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.

New input case for you: In order to compare with the previous methods, we evaluate our model on AIDA-B and other datasets. AIDA-CoNLL BIBREF14 is annotated on Reuters news articles. It contains training (AIDA-Train), validation (AIDA-A) and test (AIDA-B) sets.

ACE2004 BIBREF15 is a subset of the ACE2004 Coreference documents.

MSNBC BIBREF16 contains top two stories in the ten news categories(Politics, Business, Sports etc.)

AQUAINT BIBREF17 is a news corpus from the Xinhua News Service, the New York Times, and the Associated Press.

WNED-CWEB BIBREF18 is randomly picked from the FACC1 annotated ClueWeb 2012 dataset.

WNED-WIKI BIBREF18 is crawled from Wikipedia pages with its original hyperlink annotation.
Question: What datasets used for evaluation?
Output:
AIDA-B ACE2004 MSNBC AQUAINT WNED-CWEB WNED-WIKI