You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
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.

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
Why? Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.

New input: Methodology ::: Corpus-based Approach
Contextual information is informative in the sense that, in general, similar words tend to appear in the same contexts. In the corpus-based approach, we capture both of these characteristics and generate word embeddings specific to a domain. Methodology ::: Dictionary-based Approach
In Turkish, there do not exist well-established sentiment lexicons as in English. In this approach, we made use of the TDK (Turk Dil Kurumu - "Turkish Language Institution") dictionary to obtain word polarities.
Question: What word-based and dictionary-based feature are used?
Solution:
generate word embeddings specific to a domain TDK (Turk Dil Kurumu - "Turkish Language Institution") dictionary to obtain word polarities