Option 1 - Give the computer a rule: If you are able to narrow down what content it is that you would like to keep, the obvious criteria that sticks out to me is the exclusion of special characters, then you can filter your results based on this.
So let's say you agree that all "good lines" will be without special characters ('/', '-', and '=') for example, if a line DOES contain one of these items, you know you can remove it from the content you are keeping. This could be done in a for loop containing an if-then condition that looks something like this..
var lineArray = //code needed to make each line of the file an element of the array
For (cnt = 0; cnt < totalLines; cnt++)
{
var line = lineArray[cnt];
if (line.contains("/") || line.contains("-") || line.contains("="))
lineArray[cnt] = "";
}
At the end of this code you could simply get all the text within the array and it would no longer contain the unwanted lines. If there are unwanted lines however, that are virtually indistinguishable by characters, length, positioning etc. the previous approach begins to break down on some of the trickier lines.
This is because there is no rule you can give the computer to distinguish between the good and the bad without giving it a brain such as yours that recognizes parts of speech and sentence structure. In which case you might consider option 2, which is just that.
Option 2- Give the computer a brain: Given that the text you want to remove will more or less be incoherent documentation based on what you have shown us, an open source (or purchased) natural language processor may be what you are looking for.
I found a good beginner's intro at http://myreaders.info/10_Natural_Language_Processing.pdf with some information that might be of use to you. From the source,
"Linguistics is the science of language. Its study includes:
- sounds (phonology),
- word formation (morphology),
- sentence structure (syntax),
- meaning (semantics), and understanding (pragmatics) etc.
Syntactic Analysis : Here the analysis is of words in a sentence to know the grammatical structure of the sentence. The words are transformed into structures that show how the words relate to each others. Some word sequences may be rejected if they violate the rules of the language for how words may be combined. Example: An English syntactic analyzer would reject the sentence say : 'Boy the go the to store.' "
Using some sort of NLP, you can discover whether a given section of text contains a sentence or some incoherent rambling. This test could then be used as a filter in your program for what you would like to keep or remove.
Side note- As it appears your sample text is not just sentences but literature, sometimes characters will speak in sentence fragments as part of their nature given by the author. In this case, you could add a separate condition that if the text is contained within two quotations and has no special characters, you want to keep the text regardless.
In the end NLP may be more work than you require or that you want to do, in which case Option 1 is likely going to be your best bet. On the other hand, it may be just the thing you are looking for. Whatever the case or if you decide you need some combination of the two, best of luck! I hope this answer helps.