def test_kb_valid_entities(nlp):
"""Test the valid construction of a KB with 3 entities and two aliases"""
mykb = KnowledgeBase(nlp.vocab, entity_vector_length=3)
# adding entities
mykb.add_entity(entity="Q1", freq=0.9, entity_vector=[8, 4, 3])
mykb.add_entity(entity="Q2", freq=0.5, entity_vector=[2, 1, 0])
mykb.add_entity(entity="Q3", freq=0.5, entity_vector=[-1, -6, 5])
# adding aliases
mykb.add_alias(alias="douglas", entities=["Q2", "Q3"], probabilities=[0.8, 0.2])
mykb.add_alias(alias="adam", entities=["Q2"], probabilities=[0.9])
# test the size of the corresponding KB
assert mykb.get_size_entities() == 3
assert mykb.get_size_aliases() == 2
# test retrieval of the entity vectors
assert mykb.get_vector("Q1") == [8, 4, 3]
assert mykb.get_vector("Q2") == [2, 1, 0]
assert mykb.get_vector("Q3") == [-1, -6, 5]
# test retrieval of prior probabilities
assert_almost_equal(mykb.get_prior_prob(entity="Q2", alias="douglas"), 0.8)
assert_almost_equal(mykb.get_prior_prob(entity="Q3", alias="douglas"), 0.2)
assert_almost_equal(mykb.get_prior_prob(entity="Q342", alias="douglas"), 0.0)
assert_almost_equal(mykb.get_prior_prob(entity="Q3", alias="douglassssss"), 0.0)
def test_vocab_serialization(nlp):
"""Test that string information is retained across storage"""
mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
# adding entities
mykb.add_entity(entity="Q1", freq=27, entity_vector=[1])
q2_hash = mykb.add_entity(entity="Q2", freq=12, entity_vector=[2])
mykb.add_entity(entity="Q3", freq=5, entity_vector=[3])
# adding aliases
mykb.add_alias(alias="douglas",
entities=["Q2", "Q3"],
probabilities=[0.4, 0.1])
adam_hash = mykb.add_alias(alias="adam",
entities=["Q2"],
probabilities=[0.9])
candidates = mykb.get_alias_candidates("adam")
assert len(candidates) == 1
assert candidates[0].entity == q2_hash
assert candidates[0].entity_ == "Q2"
assert candidates[0].alias == adam_hash
assert candidates[0].alias_ == "adam"
with make_tempdir() as d:
mykb.to_disk(d / "kb")
kb_new_vocab = KnowledgeBase(Vocab(), entity_vector_length=1)
kb_new_vocab.from_disk(d / "kb")
candidates = kb_new_vocab.get_alias_candidates("adam")
assert len(candidates) == 1
assert candidates[0].entity == q2_hash
assert candidates[0].entity_ == "Q2"
assert candidates[0].alias == adam_hash
assert candidates[0].alias_ == "adam"
assert kb_new_vocab.get_vector("Q2") == [2]
assert_almost_equal(kb_new_vocab.get_prior_prob("Q2", "douglas"), 0.4)