Text Spinner using Naive Bayes

Question

I am writing a text spinner which is working fine as it should. But the accuracy of the readable sentences is very low as it is just using a dictionary which i am getting from database. Which return spintax like this

{Your} {home| house| residence| property} {is} {your} {castle| mansion| fortress| palace}

and is passed to a function which selects randomly synonym and output sentence based on the original input of the user. For example for input:

Your home is your castle.

will return

Your property is your mansion.

Now I want to include Artificial intelligence as it will make my output sentences more readable. I want to know how to make a better selection using naive Bayes. I know I probably need to train so that better results.

Here is my current method for selection of word, which is really simple right now.

def spin(spintax):
    while True:
        word, n = re.subn('{([^{}]*)}',lambda m: random.choice(m.group(1).split("|")),spintax)
        if n == 0: break
return word.strip()

Thank you in advance if you guys need me to post more code let me know

Answer 1

This will probably get closed as there is no concise answer to your question, but you might want to check out nltk wordnet:

https://pythonprogramming.net/wordnet-nltk-tutorial/