OSError: [E050] in nlp.initialize()

I am trying to train an entity linker but I am getting the error

OSError: [E050] Can't find model 'corpus/en_vectors'. It doesn't seem to be a Python package or a valid path to a data directory.

in initialize().

I’ve looked at the docs here, but am struggling to see why the error is occurring.

How to reproduce the behaviour

from spacy.kb import KnowledgeBase
from spacy.training import Example
import spacy

nlp = spacy.load('en_core_web_lg')
# here I usually load my local vocab path, but the same error occurs without this
# nlp.vocab.from_disk(self.vocab_path)
nlp.vocab.vectors.name = "spacy_pretrained_vectors"

def create_kb(vocab):
    entity_vector_length = 300
    kb = KnowledgeBase(vocab=vocab, entity_vector_length=entity_vector_length)
    # here I usually load my local knowledge base, but the same error occurs if you dont add anything 
    # kb.from_disk(self.kb_path)
    return kb

entity_linker = nlp.add_pipe("entity_linker")
entity_linker.set_kb(create_kb)

train_data = []
text_1 = "Russ Cochran his reprints include EC Comics."
dict_1 = {(0, 12): {"Q7381115": 1.0, "Q2146908": 0.0}}
train_data.append((text_1, {"links": dict_1}))
text_2 = "Russ Cochran has been publishing comic art."
dict_2 = {(0, 12): {"Q7381115": 1.0, "Q2146908": 0.0}}
train_data.append((text_2, {"links": dict_2}))
text_3 = "Russ Cochran captured his first major title with his son as caddie."
dict_3 = {(0, 12): {"Q7381115": 0.0, "Q2146908": 1.0}}
train_data.append((text_3, {"links": dict_3}))
text_4 = "Russ Cochran was a member of University of Kentucky's golf team."
dict_4 = {(0, 12): {"Q7381115": 0.0, "Q2146908": 1.0}}
train_data.append((text_4, {"links": dict_4}))

examples = []
for text, annotation in train_data:
    doc = nlp.make_doc(text)
    example = Example.from_dict(doc, annotation)
    examples.append(example)

other_pipes = [pipe for pipe in nlp.pipe_names if pipe != "entity_linker"]
with nlp.select_pipes(disable=other_pipes):
    optimizer = nlp.initialize()
    for itn in range(n_iter):
        random.shuffle(examples)
        losses = {}
        batches = minibatch(examples, size=compounding(4.0, 32.0, 1.001))
        for batch in batches:
            nlp.update(
                batch, drop=0.2, losses=losses, sgd=optimizer,
            )

I’m getting this same issue when I try to load my own knowledge base and vocab. For this I thought maybe I needed to change the config file to point to the correct vectors location (which is “local_kb_path/vocab/vectors”), so I tried:

config = {"initialize": {"vectors": 'local_kb_path/vocab/vectors'}}
entity_linker = nlp.add_pipe("entity_linker", config=config)

but this gives ‘extra fields not permitted’.

Many thanks!

Your Environment

• spaCy version: 3.0.0rc2
• Platform: Darwin-18.6.0-x86_64-i386-64bit
• Python version: 3.7.9
• Pipelines: en_core_web_md (3.0.0a0), en_core_web_lg (3.0.0a0)

[svlandeg]

Sounds good! I’ll close this in the meantime, but feel free to reopen or open a new issue if you can’t get it to work. (for usage questions, you can also use our new discussion board btw! https://github.com/explosion/spaCy/discussions)

[lizgzil]

Thank you @svlandeg I will let you know how I get on with that advice 👍