openwound | writing tool that uses analyzed parts

The pre-trained word vector data needed for the Word2Vec module is not distributed with this project. It's an 822 MB download. For information on the Wikipedia 2014 + Gigaword 5 GloVe set, visit the Stanford Natural Language Processing Group glove page. Download it directly here. You'll probably want the glove.6B.50d.txt file, though you can experiment with the larger sets if you like. Place the glove.6B.50d.txt file in the /data directory.
Accept any amount of text from a field called INPUT. Perform a part-of-speech tagging and display the tagged words in a text field called TAGGED OUTPUT. The value of the TAGGED OUTPUT field might look/NN something/NN like/IN this/DET ./PP
Copy each word (without its POS tag) into an appropriate field based on it.s part-of-speech. The user may delete words or add their own words. Make all words lowercase.
Accept a value the user has inputed in the COMMON field. The value can be from 0-100. The number corresponds to an array that contains the 1000 most common words in the English language. (For example, a value of 20 in the COMMON text field means the 20 most common words will not be substituted in the next step.)
Substitute each of the words or punctuation marks in the TAGGED OUTPUT field with a different word or punctuation mark from the corresponding POS field unless that word is in the range specified by the COMMON value in which case it is not substituted. Display the result in a SUBSTITUTION text field.
Capitalize any letter directly following the PP, Punctuation, Sentence Ender tag then remove the POS tags from the SUBSTITUTION text. Display the new text in a field called RECOMBINED.