English verbs processing ending with 'e'

Question

I am implementing few string replacers, with these conversions in mind

'thou sittest' → 'you sit'
'thou walkest' → 'you walk'
'thou liest' → 'you lie'
'thou risest' → 'you rise'

If I keep it naive it is possible to use regex for this case to find & replace, like thou [a-z]+est

But the trouble comes in English verbs that end with e because based on the context I need to trim the est in some & trim just st in the rest

What is the quick-dirty solution to achieve this?

Answer 1

Probably the most quick and dirty:

import nltk
words = set(nltk.corpus.words.words())
for old in 'sittest walkest liest risest'.split():
    new = old[:-2]
    while new and new not in words:
        new = new[:-1]
    print(old, new)

Output:

sittest sit
walkest walk
liest lie
risest rise

UPDATE. A slightly less quick and dirty (works e.g. for rotest → verb rot, not noun rote):

from nltk.corpus import wordnet as wn
for old in 'sittest walkest liest risest rotest'.split():
    new = old[:-2]
    while new and not wn.synsets(new, pos='v'):
        new = new[:-1]
    print(old, new)

Output:

sittest sit
walkest walk
liest lie
risest rise
rotest rot