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.

[EX Q]: We collect utterances from the $\mathbf {C}$hinese $\mathbf {A}$rtificial $\mathbf {I}$ntelligence $\mathbf {S}$peakers (CAIS), and annotate them with slot tags and intent labels. The training, validation and test sets are split by the distribution of intents, where detailed statistics are provided in the supplementary material. Since the utterances are collected from speaker systems in the real world, intent labels are partial to the PlayMusic option. We adopt the BIOES tagging scheme for slots instead of the BIO2 used in the ATIS, since previous studies have highlighted meaningful improvements with this scheme BIBREF30 in the sequence labeling field. 
 Question: What is the source of the CAIS dataset?
[EX A]: the $\mathbf {C}$hinese $\mathbf {A}$rtificial $\mathbf {I}$ntelligence $\mathbf {S}$peakers (CAIS)

[EX Q]: We also measure the usage of words related to people's core values as reported by Boyd et al. boyd2015. The sets of words, or themes, were excavated using the Meaning Extraction Method (MEM) BIBREF10 . 
 Question: How do they obtain psychological dimensions of people?
[EX A]: using the Meaning Extraction Method

[EX Q]: As a first corpus, we compiled INLINEFORM0 that represents a collection of 80 excerpts from scientific works including papers, dissertations, book chapters and technical reports, which we have chosen from the well-known Digital Bibliography & Library Project (DBLP) platform. As a second corpus, we compiled INLINEFORM0 , which represents a collection of 1,645 chat conversations of 550 sex offenders crawled from the Perverted-Justice portal. As a third corpus, we compiled INLINEFORM0 , which is a collection of 200 aggregated postings crawled from the Reddit platform. 
 Question: What size are the corpora?
[EX A]:
80 excerpts from scientific works collection of 1,645 chat conversations collection of 200 aggregated postings