NER component in en_core_web_trf doesn't depend on transformer

[frankier]

How to reproduce the behaviour

I just wanted entities so I thought I would only enable NER in case it goes a bit faster.

import spacy
nlp = spacy.load("en_core_web_trf", enable=["ner"])
results = nlp("I went to France for a coffee with Francois")
for ent in results.ents:
    print(ent.text, ent.label_)

It looks like the outputs are just that subsequent bigrams is ORDINAL:

I went ORDINAL
to France ORDINAL
for a ORDINAL
coffee with ORDINAL

The problem goes away when I enable transformer:

import spacy
nlp = spacy.load("en_core_web_trf", enable=["ner", "transformer"])
results = nlp("I went to France for a coffee with Francois")
for ent in results.ents:
    print(ent.text, ent.label_)

Output:

France GPE
Francois PERSON

I suppose ner should depend upon transformer.

Your Environment

• Operating System: Linux
• Python Version Used: 3.11.7
• spaCy Version Used: 3.7.2
• Environment Information:

[svlandeg]

Hi! Let me transfer this thread to the discussion forum and follow up there.