I am following Stata package to run the did_imputation of Borusyak,2021 in using the DiD imputation estimator
The normal DiD estimator in their regression is



did_imputation Y i t Ei [if] [in] [estimation weights] [, options]

where

Y outcome variable
i variable for unique unit id
t variable for calendar period
Ei variable for unit-specific date of treatment (missing = never-treated)


In triple diffs, they define that

22) Triple-diffs:
When observations are defined by i,g,t when, say, i are counties and g are age groups, specify a variable ig identifying the (i,g) pairs as the unit identifier, add appropriate
FEs, and choose your clustering level, e.g.:
. did_imputation Y ig t Eig, fe(ig i#t g#t) cluster(i) ...

Note that the event time Eig should be specific to the i,g pairs, not to the i. For instance, Eig is missing for a never-treated age group in a county where other groups are
treated at some point.

I am wondering the difference here is the difference of one subsample from another subsample or the difference of one subsample from the whole sample? Saying for an example, in my research, i is firm and g is developed and developing countries. So when using this approach, the tau retrieved from the regression is the difference between developed and developing countries or the difference between developed countries compared to the whole sample.