French morphologizer mislabeling future, conditional, imperative

[KennethBaclawskiJrDialpad]

Hello,

I'm using spaCy to model French conversations, and I see that the morphologizer is not performing as well as I'd expect for unambiguous irrealis forms (specifically future tense, conditional mood, imperatives). I understand the underlying reason is probably that these forms aren't frequent in the training data, but are there any potential updates or recommended workarounds?

For example:

• "Remplacez le verbe par un nom.": The imperative "Remplacez" is misrecognized as a noun (using POS/TAG). This is similar to [French morphologizer] Mislabelisation of Mood=Imp|Number=Sing|Tense=Present #8147, but broader in that "Remplacez" is unambiguously a verb.
• "Vous remplacerez le verbe par un nom.": The future tense "remplacerez" is misrecognized as an imperative (MORPH contains Mood=Imp, Tense=Pres), even though it is unambiguously the future.
• "Vous remplaceriez le verbe par un nom.": The conditional mood "remplaceriez" is misrecognized as the future tense (MORPH contains Mood=Ind, Tense=Fut), even though it is unambiguously the conditional.

I'm working with a set of ~160 common French verbs and tested their whole paradigms in this way. 98% of infinitives are recognized correctly, but only 13% of second person plural imperatives (34% even had incorrect POS like in the example above), 37% of future tense, and 7% of conditional mood forms. Sure enough, I see that these three categories are uncommon in the UD French Sequoia data.

How to reproduce the behaviour

import spacy
nlp = spacy.load("fr_core_news_sm")
doc = nlp("Remplacez le verbe par un nom.")

for token in doc:
    print(token.text, token.pos_, token.morph)

Info about spaCy

spaCy version: 3.8.2
Python version: 3.11.9
Pipelines: fr_core_news_sm (3.8.0)