Part 1. 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.
Part 2. 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?
Answer: No
Explanation: Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.
Part 3. Exercise
The main contribution of our work is thus a new parallel data-to-text NLG corpus that (1) is more conversational, rather than information seeking or question answering, and thus more suitable for an open-domain dialogue system, (2) represents a new, unexplored domain which, however, has excellent potential for application in conversational agents, and (3) has high-quality, manually cleaned human-produced utterances.
Question: How the authors made sure that corpus is clean despite being crowdsourced?
Answer:
manually cleaned human-produced utterances