Bugzilla

Thanks Drew! 
1) Could you please give me some idea as to what level of prefix (partial city name) you want to match.
 E.g. `sunnyvale` &  `sunnyval` are good.
or do you want that to match `sunnyva` ?
is there minimum length of prefix for city name that you would expect to have a match.
This could be crucial information. As we train this model we could show such examples but at the sametime we don't want the model to learn noise. as in `is the weather sunny ?` as city prefix.

A good trade off would be you won't get 100% prefix match of sqlite (fts) but at the sametime the number of such partial examples need to be kept minimal otherwise model will pick noise. 
Please let me know your thoughts.

Thanks Drew! 
1) Could you please give me some idea as to what level of prefix (partial city name) you want to match.
 E.g. `sunnyvale` &  `sunnyval` are they good?
or do you want that to match `sunnyva` ?
is there minimum length of prefix for city name that you would expect to have a match.
This could be crucial information. As we train this model we could show such examples but at the sametime we don't want the model to learn noise. as in `is the weather sunny ?` as city prefix.

A good trade off would be you won't get 100% prefix match of sqlite (fts) but at the sametime the number of such partial examples need to be kept minimal otherwise model will pick noise. 
Please let me know your thoughts.

Thanks Drew! 
1) Could you please give me some idea as to what level of prefix (partial city name) you want to match.
 E.g. `sunnyvale` &  `sunnyval`  - are they good?
or do you want that to match `sunnyva` ?
is there minimum length of prefix for city name that you would expect to have a match.
This could be crucial information. As we train this model we could show such examples but at the sametime we don't want the model to learn noise. as in `is the weather sunny ?` as city prefix.

A good trade off would be you won't get 100% prefix match of sqlite (fts) but at the sametime the number of such partial examples need to be kept minimal otherwise model will pick noise. 
Please let me know your thoughts.