After being exposed to two views regarding verbal aspect, I was exposed to several new fields of linguistics, where more was done in the areas of statistics and analyzing large data sets. Corpus Linguistics was one of these fields. Here, large corpora (bodies) of literature are compiled and then marked so that every item that a researcher wishes to search for gets a tag. Search engines then search for tags and report the text that is associated with the tag. A large part of the work is to manually verify the tags in order to ensure reliability of the search finding appropriate text. Since the search engine can only find material through its tags, it is quite important to have accurate tags.
Next, it is important to search for an item in the corpora relevant to some other item. These items can be grammatical, lexical, or structural. One could tag almost anything and then have a search engine look for it. My hope is to build a corpora of Greek Letters (Epistles) that is tagged for tense, mood, aspect, lexical items. and lexical morphemes. Currently several software packages do most of these things, such as Logos, Bibleworks, and Perseus Digital Library, but none of them tag everything relevant to this purpose. Search engines already exist that can perform the searches, but the corpora as such does not yet exist. Besides the tags, the individual letters have not yet been collected into a large database.
The problem with all of their tag systems is that none of them tag aspect or specific morphemes for separate analysis. One cannot set up any of their engines to locate where a perfective verb is collocated with a temporal adverb, because the verbs are no so marked. While one could set up a search for a particular tense-form and a certain adverb, this forces the search to be divided by tense-form paradigms rather than by aspectual category, based on their respective morphemes. Also certain adjectives and adverbs contain verbal aspect morphemes that also behave like those in verbs, but currently no way exists to search for specifically those items to compare them in analysis. I am hoping that what I put together will be a step forward for future research in this area.