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.
One 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?
Solution is here: No
Explanation: Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.

Now, solve this: The focus of this publication is on representing information that is valuable for these tasks but that hitherto has largely been ignored in machine learning approaches centering around simplified language, specifically, text structure (e.g., paragraphs, lines), typography (e.g., font type, font style), and image (content, position, and dimensions) information. Information on physical page segmentation (for PDFs only), paragraph segmentation, and line segmentation was added as part of a textspan element in the textstructure layer
Question: Which information about text structure is included in the corpus?
Solution:
paragraphs lines Information on physical page segmentation (for PDFs only), paragraph segmentation, and line segmentation