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.
--------
Question: We draw on a recently released corpus of state speeches delivered during the annual UN General Debate that provides the first dataset of textual output from states that is recorded at regular time-series intervals and includes a sample of all countries that deliver speeches BIBREF11 .  
 Question: Which dataset do they use?

Answer: corpus of state speeches delivered during the annual UN General Debate


Question: 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?

Answer: using the Meaning Extraction Method


Question: Methods ::: Combining the two methods
We further propose to use the two methods together to combine their strengths. In fact, while the length token acts as a soft constraint to bias NMT to produce short or long translation with respect to the source, actually no length information is given to the network. On the other side, length encoding leverages information about the target length, but it is agnostic of the source length. 
 Question: Do they experiment with combining both methods?

Answer:
Yes