@@ -36,6 +36,8 @@ In order to have a good working State machine we need to first update the gramma
#### n-Grams checker
This checker used the crawled data and gave a score by summing up all the n_grams probabilities of phrases in a sentence.
### Proof of Effictiveness
In order to show the effictiveness of our tool we used ChatGBT to write a script that is using a third-party Python library to make the exact same score for each sentence. These can be found in CheckerCorrector/samples/ directory. Both Json generated by our tool and the third party are available.
### Corrector
The current corrector uses the typo corrector which was used in the checker and also the state machine to suggest possible corrections. Corrections of the typo corrector are based on the most similar path through the state machine. In order to find a similar path we are first doing a DFS on the graph starting from the first token and storing all the possible paths. Then, based on the most similar path we decide whether we should change/delete/add a token and suggest a token with a similar role.