spaCy/spacy/sandbox_test_sofie/testing_el.py
2019-03-21 17:33:25 +01:00

72 lines
1.9 KiB
Python

# coding: utf-8
import spacy
from spacy.kb import KnowledgeBase
def create_kb():
mykb = KnowledgeBase()
print("kb size", len(mykb), mykb.get_size_entities(), mykb.get_size_aliases())
print()
# adding entities
entity_0 = "Q0" # douglas adams
print(" adding entity", entity_0)
mykb.add_entity(entity_id=entity_0, prob=0.5)
entity_42 = "Q42" # douglas adams
print(" adding entity", entity_42)
mykb.add_entity(entity_id=entity_42, prob=0.5)
entity_5301561 = "Q5301561"
print(" adding entity", entity_5301561)
mykb.add_entity(entity_id=entity_5301561, prob=0.5)
print("kb size", len(mykb), mykb.get_size_entities(), mykb.get_size_aliases())
print()
# adding aliases
alias1 = "douglassss"
print(" adding alias", alias1, "to Q42 and Q5301561")
mykb.add_alias(alias=alias1, entities=["Q42", "Q5301561"], probabilities=[0.8, 0.2])
alias3 = "adam"
print(" adding alias", alias3, "to Q42")
mykb.add_alias(alias=alias3, entities=["Q42"], probabilities=[0.9])
print("kb size", len(mykb), mykb.get_size_entities(), mykb.get_size_aliases())
print()
return mykb
def add_el(kb):
nlp = spacy.load('en_core_web_sm')
print("pipes before:", nlp.pipe_names)
el_pipe = nlp.create_pipe(name='el', config={"kb": kb})
nlp.add_pipe(el_pipe, last=True)
print("pipes after:", nlp.pipe_names)
print()
text = "The Hitchhiker's Guide to the Galaxy, written by Douglas Adams, reminds us to always bring our towel."
doc = nlp(text)
for token in doc:
print("token", token.text, token.ent_type_, token.ent_kb_id_)
print()
for ent in doc.ents:
print("ent", ent.text, ent.label_, ent.kb_id_)
print()
for alias in ["douglassss", "rubbish", "adam"]:
candidates = nlp.linker.kb.get_candidates(alias)
print(len(candidates), "candidates for", alias)
if __name__ == "__main__":
mykb = create_kb()
add_el(mykb)