I often need to take dense blocks of texts and convert them into slightly more standardized and easily understood formats (eg, spelling out abbreviations, creating spacing where there had been none prior). Is there a natural language processing or other tool that takes such inputs and transforms them in a way that lets me specify the structure of the output (provided that I give it a dictionary of abbreviations and other key words, etc)?
As an example, I might need to convert information that looks like this
- DEAL DTLS: $311.340mm Auto (OMAOT)
- ESTABLISHERS: Decidedly SP (str.), BMB
- CLS $AMT(mm) S&P C/E % WIN WAL(1)
- A 254.640 AA 51.00 1-16 0.22
and transform into this:
- Details of the Deal: $311m Auto Bond
- Ticker: OMAOT
- Establishers: Decidedly Business Co. (structuring), Bank of Bob
- Class / Amount ($m) / S&P / Credit Enhancement % / Window / Weighted Average Life
- A / 254.640 / AA / 51.00 / 1-16 / 0.22
PS I know that this can be accomplished in Python with some time and energy. I'm not a coder, however, and am hoping that someone has already created an open source tool that does such things.
