I was wondering if there is some simple way to obtain the same tags provided by a Prodigy recipe through a custom pipeline component in Spacy? I'm guessing this is a process that happens under the hood in Prodigy.
For example, say I'd like to have a Spacy custom pipeline component that gave me the same initial tags that are given by, using one of your recipe examples,
prodigy coref.manual coref_movies en_core_web_sm ./plot_summaries.jsonl --label COREF
Thank you
Hi! I'm not 100% sure I understand the question correctly, do you have a more specific example? Do you want to train a pipeline component that assigns coreference relationships annotated in Prodigy?
Apologies if I wasn't clear! I'm trying to get the same exact tags through SpaCy Matcher to those provided by a prodigy recipe.
For example, in SpaCy I'm doing:
nlp = spacy.load("en_core_web_lg")
matcher = Matcher(nlp.vocab)
pattern_np = [
{"POS": "DET", "TAG": {"NOT_IN": ["PRP$"]}, "OP": "?"},
{"POS": "ADJ", "OP": "*"},
{
"POS": {"IN": ["PROPN", "NOUN"]},
"OP": "+",
"ENT_TYPE": {"NOT_IN": ["PERSON", "ORG"]},
},
]
pattern_prn = [{'POS':'PRON'}]
matcher.add("NP", [pattern_np])
matcher.add('PRN', [pattern_prn])
I copied the NP pattern from the recipes/coref.py file as suggested in another post.
Now for example:
doc = nlp("Eddie fought the wild rabid wolves with Pickles the husky. He was a good boy.")
matches = matcher(doc)
for match_id, start, end in matches:
string_id = nlp.vocab.strings[match_id] # Get string representation
span = doc[start:end] # The matched span
print(string_id, start, end, span.text)
for ent in doc.ents:
start = doc.ents[0].start
end = doc.ents[0].end
span = doc[start:end]
print('ENT({})'.format(doc.ents[0].label_), start, end, ent)
Which gives me as output:
NP 2 6 the wild rabid wolves
NP 3 6 wild rabid wolves
NP 4 6 rabid wolves
NP 5 6 wolves
NP 7 8 Pickles
PRN 11 12 He
NP 13 16 a good boy
NP 14 16 good boy
NP 15 16 boy
ENT(PERSON) 0 1 Eddie
In here I notice that if there are nested NP spans, the NP that Prodigy gives me is the longest NP span (eg. the wild rabid wolves). Also, I might be missing some POS patterns that are not explicit in coref.py.
Ideally I'd like to have the exact Match patterns to those of a recipe like:
prodigy coref.manual coref_movies en_core_web_lg ./plot_summaries.jsonl --label COREF`
Which gives me:
So I was just wondering if there's some functionality to obtain the Matcher used in a recipe.
Ahhh okay, thanks for the clarification! 
The pattern defined in coref.py is the only pattern used by the workflow. By default, the recipe also includes named entities (so everything in the doc.ents) and optionally, noun chunks (everything in doc.noun_chunks).
The filter_spans helper lets you filter a list of spans to only keep the (first) longest matches. This is also what Prodigy uses under the hood. Together, this should give you the same results as the coref recipe suggestion 
Great, thank you!
