CODEWITHSUNDEEP
pythonspacy
user3268362
user3268362

Reputation: 259

Unable to create a custom entity type/label using Matcher in Spacy 2

I am trying to create a custom entity label called FRUIT using the rule-based Matcher (i.e. adding on_match rules), following the spaCy guide. I'm using spaCy 2.0.11, so I believe the steps to do so have changed compared to spaCy 1.X

Example: doc = nlp('Tom wants to eat some apples at the United Nations')
Expected text and entity outputs:

Tom PERSON
apples FRUIT
the United Nations ORG

However, I seem to get the following error: [E084] Error assigning label ID 7429577500961755728 to span: not in StringStore. I have included my code below. When I change nlp.vocab.strings['FRUIT'] to nlp.vocab.strings['EVENT'], strangely it works but apples would be assigned the entity label EVENT. Anyone else encountering this issue? 

doc = nlp('Tom wants to eat some apples at the United Nations')

FRUIT = nlp.vocab.strings['FRUIT']

def add_ent(matcher, doc, i, matches):
    # Get the current match and create tuple of entity label, start and end.
    # Append entity to the doc's entity. (Don't overwrite doc.ents!)
    match_id, start, end = matches[i]    
    doc.ents += ((FRUIT, start, end),)

matcher = Matcher(nlp.vocab)
pattern = [{'LOWER': 'apples'}]
matcher.add('AddApple', add_ent, pattern)

matches = matcher(doc)

for ent in doc.ents:
    print(ent.text, ent.label_)

Upvotes: 0

Views: 882

Answers (1)

user3268362
user3268362

Reputation: 259

Oh okay, I think I found a solution. The label has to be added to nlp.vocab.strings if it is not there:

nlp.vocab.strings.add('FRUIT')

Upvotes: 5

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