In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

[Q]: We extracted Japanese word pairs from the Evaluation Dataset of Japanese Lexical Simplification kodaira.
[A]: where does the data come from?

[Q]: Both systems were optimized on the tst2014 using Minimum error rate training BIBREF20 . A detailed description of the systems can be found in BIBREF21 .
[A]: How is the PBMT system trained?

[Q]: We therefore use reduction in softmax probability of the correct relation as our signaling strength metric for the model. We call this metric ${\Delta }_s$ (for delta-softmax), which can be written as:

where $rel$ is the true relation of the EDU pair, $t_i$ represents the token at index $i$ of $N$ tokens, and $X_{mask=i}$ represents the input sequence with the masked position $i$ (for $i \in 1 \ldots N$ ignoring separators, or $\phi $, the empty set).
[A]:
How is the delta-softmax calculated?