lemmatization issue

[MaJaPers]

I would expect the outcome of a lemmatization of a verb to be the dictionary form of it (i.e. (Mood: [indicative], Number: [singular], Person: [first], Tense: [present], VerbForm: [finite], Voice: [active]). However cltk does produce that outcome, even if it able to correctly determine the 'mood'. 'videtur' gives 'videtur' instead of 'video'.

from cltk import NLP
cltk_nlp = NLP(language="lat",suppress_banner=True)
cltk_nlp.analyze('videtur').lemmata

>>> 'videtur'

Similar applies to nouns - plurals, I guess, should be lemmatized to singulars. 'verba' gives 'verba' instead of 'verbum'.

from cltk import NLP
cltk_nlp = NLP(language="lat",suppress_banner=True)
cltk_nlp.analyze('verba').lemmata

>>> 'verba'

However, LatinBackoffLemmatizer works:

from cltk.lemmatize.lat import LatinBackoffLemmatizer

lemmatizer = LatinBackoffLemmatizer()
lemmatizer.lemmatize(['videtur'])

>>> [('videtur', 'video')]

lemmatizer.lemmatize(['verba'])

>>> [('verba', 'verbum')]

Other latin lemmatizers also manage to do it:
```python
from lamonpy import Lamon
lamon=Lamon()
score,tagged=lamon.tag('videtur')[0]
tagged[0][2]

>>> 'video'

import simplemma
simplemma.lemmatize('videtur',lang='la')

>>> 'video'

from lamonpy import Lamon
lamon=Lamon()
score,tagged=lamon.tag('verba')[0]
tagged[0][2]

>>> 'verbum'

import simplemma
simplemma.lemmatize('verba',lang='la')

>>> 'verbum'