Comments (3)
It determines the content in _deletes
dictionary. The keys are the edit candidates generated by only deletes which are within an edit distance of 1 to max_edit_distance_dictionary
of the original words. The dictionary values are lists of suggested correction words.
For example, with a max_edit_distance_dictionary = 1
, _deletes
contains
'{te': ['the'], 'he': ['the'], 'the': ['the'], 'th': ['the']}
and when max_edit_distance_dictionary = 2
, _deletes
contains
'h': ['the'], 'e': ['the'], 'he': ['the'], 'th': ['the'], 't': ['the'], 'te': ['the'],
'the': ['the']}
"h", "e" and "t" were not previously included since they can only be obtained by making 2 deletes (edits) from the original word "the".
prefix_length
also plays a part in generating _deletes
since it limits the "original word" from which we make deletes. For example, when prefix_length = 7
, "unhpi" can be mapped to "unhappiness" since it's 2 deletes from "unhappi".
So we enforce max_edit_distance <= max_edit_distance_dictionary
since _deletes
will contain any mapping with an edit distance greater then max_edit_distance_dictionary
. There was also a mistake in _edits_prefix()
,
if len(key) > self._max_dictionary_edit_distance:
should have been
if len(key) > self._prefix_length:
I'm sorry if that caused this confusion.
from symspellpy.
Thanks, it is very clear now. So _edits_prefix() will be fixed in the later version, right?
from symspellpy.
The changes has been pushed to the dev
branch, I'll merge it to master
later. Interestingly, it does not seem to affect the accuracy of the program since having a stop index larger then the string length is handled gracefully in python. For example
s = "abc"
print(s[: 10])
gives
abc
which is what _edits_prefix()
wanted.
from symspellpy.
Related Issues (20)
- ignore_term_with_digits doesn't work HOT 2
- replaced_words is not correct HOT 4
- Correction doesn't prioritize bigram. HOT 3
- Predicts garbage for Bengali input HOT 7
- wrong word segmentation result HOT 1
- First line of the text file reads wrong HOT 4
- edit distance issue HOT 1
- Substring search
- error if i use spell checker to my dataset HOT 4
- How to empty the dictionary quickly HOT 3
- Custom Edit Distance HOT 2
- Using a custom dictionary with the desired correction HOT 1
- the frequency in the loaded dictionary is absolute, not relative
- Incompatible architecture on macOS
- Keep spacing in between words and not split on white space HOT 1
- is_acronym only detects numbers if match_any_term_with_digits HOT 1
- Correction not using bi-grams
- Bigrams omitted from save and load pickle methods HOT 5
- Does SymSpell has spell checker ? HOT 2
- Error when pip install on MacOS HOT 7
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