MCScript2.0: A Machine Comprehension Corpus Focused on Script Events and Participants
Table 1: Distribution of question labels, before validation.
['[ITALIC] text-based', '[ITALIC] script-based', '[ITALIC] text-or-script', '[ITALIC] unfitting', '[ITALIC] unknown']
In the data collection process, we crowdsourced 1,800 new texts, resulting in a total of 3,919 texts for 200 scenarios. On average, there are 1.98 target sentences per text. In the question collection, we gathered 42,132 questions that were then used for the answer collection. For 8,242 questions, there was no clear majority on the question label. 24,193 of these could be answered, i.e. 71%.