Science must be reproducible, and closely connected to experimental data. This has consequences on scientific
practice, and in particular on the how experimental resources and
copora should be dealt with, which can be translated in what I would
consider rules of scientific ethics (which are not confined to
A corpus of data should be precisely sourced and documented with all
relevant information regarding the context and means of its
creation. It should, as much as technically feasible include the initial
A corpus should not be tampered with for any reason, by anyone
including particularly its creator.
However, it is naturally permissible to "correct", reprocess,
annote, document or otherwise modify a corpus as long as all
modifications are reproducibles by anyone, thus based on processors
or separate data files that can be reapplied to the original files
to get the modified version of corpus.
In other words, any phenomenon observed when processing a corpus should be traceable by anyone,
for example to determine whether it comes from the original data or
from whatever modification was applied to the corpus. This includes
correcting what may seem obvious errors.
As long as you are transparent regarding these rules, you are free to
do as you choose, preferably justifying your choices on the basis of
your intent or technical means. Others may disagree with you, but they can then do so on an objective basis, and possibly do competing work on that same basis.
Then there is the issue of defining: what is an error? I do expect
they can be categorized to some extent, though an alleged mistake
could possibly belong to several categories. What you want to do may
depend on these categories and unless you identifies a clear misconception in the rules you have been using, I would not suggest you modify them to account for what you consider errors.
Errors are inherent to any form of information exchange and linguistic
information is no exception. Whenever possible, systematic (mechanized) error handling,
should thus be a normal component of any natural language processing
system. It has its own importance from a technological or scientific
point of view, even if it may have intrinsic limitations.
To consider a specific example, I was involved in a project that did
morphology based part-of-speech recognition to create lexicons. The
system worked pretty well on most words. But there was a statistical
dimension that caused chance errors to occur. Cases that were
considered uncertain were reviewed by hand. But whatever modifications
were made (by hand) to the raw output of the system were collected on
a file, so that they were traceable, and could also be replayed or
compared with the output of later version of the system. The idea is also that one should not correct twice the same error.
My philosophy is that anything done by hand should be minimized,
traceable, and replayable in other contexts.