word in different situation has different lemma_

[JJplane]

import spacy
nlp = spacy.load('en_core_web_sm', disable=['ner', 'parser', 'textcat'])
nlp.add_pipe(nlp.create_pipe('sentencizer'))
doc = nlp('womaned_made'.replace("_"," "))
print(doc[0].lemma_)
doc1 = nlp('womaned'.replace("_"," "))
print(doc1[0].lemma_)

the output is:

womaned
womane

so why the same word has different lemma?

• Operating System:windows 10
• Python Version Used:3.6
• spaCy Version Used:2.3.5
• Environment Information:

[svlandeg]

FYI - we converted this question to a thread on the discussion board.

We're aiming to keep the Issue tracker focused mainly on bug reports, while the new GH Discussion board can be a place where the community can come together, help eachother, discuss best practices, and so on.