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entity as one field instead of both ID and name

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This commit is contained in:
svlandeg 2019-03-25 18:10:41 +01:00
parent 46f4eb5db3
commit 8814b9010d
5 changed files with 49 additions and 66 deletions
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18
examples/pipeline/dummy_entity_linking.py
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@ -12,27 +12,27 @@ def create_kb(vocab):
kb = KnowledgeBase(vocab=vocab)
# adding entities
entity_0 = "Q1004791"
entity_0 = "Q1004791_Douglas"
print("adding entity", entity_0)
kb.add_entity(entity_id=entity_0, entity_name="Douglas", prob=0.5)
kb.add_entity(entity=entity_0, prob=0.5)
entity_1 = "Q42"
entity_1 = "Q42_Douglas_Adams"
print("adding entity", entity_1)
kb.add_entity(entity_id=entity_1, entity_name="Douglas Adams", prob=0.5)
kb.add_entity(entity=entity_1, prob=0.5)
entity_2 = "Q5301561"
entity_2 = "Q5301561_Douglas_Haig"
print("adding entity", entity_2)
kb.add_entity(entity_id=entity_2, entity_name="Douglas Haig", prob=0.5)
kb.add_entity(entity=entity_2, prob=0.5)
# adding aliases
print()
alias_0 = "Douglas"
print("adding alias", alias_0)
kb.add_alias(alias=alias_0, entities=["Q1004791", "Q42", "Q5301561"], probabilities=[0.1, 0.6, 0.2])
kb.add_alias(alias=alias_0, entities=[entity_0, entity_1, entity_2], probabilities=[0.1, 0.6, 0.2])
alias_1 = "Douglas Adams"
print("adding alias", alias_1)
kb.add_alias(alias=alias_1, entities=["Q42"], probabilities=[0.9])
kb.add_alias(alias=alias_1, entities=[entity_1], probabilities=[0.9])
print()
print("kb size:", len(kb), kb.get_size_entities(), kb.get_size_aliases())
@ -49,7 +49,7 @@ def add_el(kb, nlp):
print()
print(len(candidates), "candidate(s) for", alias, ":")
for c in candidates:
print(" ", c.entity_id_, c.entity_name_, c.prior_prob)
print(" ", c.entity_, c.prior_prob)
text = "In The Hitchhiker's Guide to the Galaxy, written by Douglas Adams, " \
"Douglas reminds us to always bring our towel. " \

15
spacy/kb.pxd
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@ -14,8 +14,7 @@ from .typedefs cimport hash_t
cdef struct _EntryC:
# The hash of this entry's unique ID and name in the kB
hash_t entity_id_hash
hash_t entity_name_hash
hash_t entity_hash
# Allows retrieval of one or more vectors.
# Each element of vector_rows should be an index into a vectors table.
@ -48,7 +47,7 @@ cdef struct _AliasC:
cdef class Candidate:
cdef readonly KnowledgeBase kb
cdef hash_t entity_id_hash
cdef hash_t entity_hash
cdef hash_t alias_hash
cdef float prior_prob
@ -97,7 +96,7 @@ cdef class KnowledgeBase:
# optional data, we can let users configure a DB as the backend for this.
cdef object _features_table
cdef inline int64_t c_add_entity(self, hash_t entity_id_hash, hash_t entity_name_hash, float prob,
cdef inline int64_t c_add_entity(self, hash_t entity_hash, float prob,
int32_t* vector_rows, int feats_row):
"""Add an entry to the knowledge base."""
# This is what we'll map the hash key to. It's where the entry will sit
@ -105,13 +104,12 @@ cdef class KnowledgeBase:
cdef int64_t new_index = self._entries.size()
self._entries.push_back(
_EntryC(
entity_id_hash=entity_id_hash,
entity_name_hash=entity_name_hash,
entity_hash=entity_hash,
vector_rows=vector_rows,
feats_row=feats_row,
prob=prob
))
self._entry_index[entity_id_hash] = new_index
self._entry_index[entity_hash] = new_index
return new_index
cdef inline int64_t c_add_aliases(self, hash_t alias_hash, vector[int64_t] entry_indices, vector[float] probs):
@ -136,8 +134,7 @@ cdef class KnowledgeBase:
self.vocab.strings.add("")
self._entries.push_back(
_EntryC(
entity_id_hash=self.vocab.strings[""],
entity_name_hash=self.vocab.strings[""],
entity_hash=self.vocab.strings[""],
vector_rows=&dummy_value,
feats_row=dummy_value,
prob=dummy_value

50
spacy/kb.pyx
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@ -5,32 +5,21 @@ from spacy.errors import Errors, Warnings, user_warning
cdef class Candidate:
def __init__(self, KnowledgeBase kb, entity_id_hash, alias_hash, prior_prob):
def __init__(self, KnowledgeBase kb, entity_hash, alias_hash, prior_prob):
self.kb = kb
self.entity_id_hash = entity_id_hash
self.entity_hash = entity_hash
self.alias_hash = alias_hash
self.prior_prob = prior_prob
@property
def entity_id(self):
"""RETURNS (uint64): hash of the entity's KB ID"""
return self.entity_id_hash
def entity(self):
"""RETURNS (uint64): hash of the entity's KB ID/name"""
return self.entity_hash
@property
def entity_id_(self):
"""RETURNS (unicode): ID of this entity in the KB"""
return self.kb.vocab.strings[self.entity_id]
@property
def entity_name(self):
"""RETURNS (uint64): hash of the entity's KB name"""
entry_index = <int64_t>self.kb._entry_index.get(self.entity_id)
return self.kb._entries[entry_index].entity_name_hash
@property
def entity_name_(self):
"""RETURNS (unicode): name of this entity in the KB"""
return self.kb.vocab.strings[self.entity_name]
def entity_(self):
"""RETURNS (unicode): ID/name of this entity in the KB"""
return self.kb.vocab.strings[self.entity]
@property
def alias(self):
@ -65,28 +54,25 @@ cdef class KnowledgeBase:
def get_size_aliases(self):
return self._aliases_table.size() - 1 # not counting dummy element on index 0
def add_entity(self, unicode entity_id, unicode entity_name=None, float prob=0.5, vectors=None, features=None):
def add_entity(self, unicode entity, float prob=0.5, vectors=None, features=None):
"""
Add an entity to the KB.
Return the hash of the entity ID at the end
"""
if not entity_name:
entity_name = entity_id
cdef hash_t id_hash = self.vocab.strings.add(entity_id)
cdef hash_t name_hash = self.vocab.strings.add(entity_name)
cdef hash_t entity_hash = self.vocab.strings.add(entity)
# Return if this entity was added before
if id_hash in self._entry_index:
user_warning(Warnings.W018.format(entity=entity_id))
if entity_hash in self._entry_index:
user_warning(Warnings.W018.format(entity=entity))
return
cdef int32_t dummy_value = 342
self.c_add_entity(entity_id_hash=id_hash, entity_name_hash=name_hash, prob=prob,
self.c_add_entity(entity_hash=entity_hash, prob=prob,
vector_rows=&dummy_value, feats_row=dummy_value)
# TODO self._vectors_table.get_pointer(vectors),
# self._features_table.get(features))
return id_hash
return entity_hash
def add_alias(self, unicode alias, entities, probabilities):
"""
@ -118,11 +104,11 @@ cdef class KnowledgeBase:
cdef vector[float] probs
for entity, prob in zip(entities, probabilities):
entity_id_hash = self.vocab.strings[entity]
if not entity_id_hash in self._entry_index:
entity_hash = self.vocab.strings[entity]
if not entity_hash in self._entry_index:
raise ValueError(Errors.E134.format(alias=alias, entity=entity))
entry_index = <int64_t>self._entry_index.get(entity_id_hash)
entry_index = <int64_t>self._entry_index.get(entity_hash)
entry_indices.push_back(int(entry_index))
probs.push_back(float(prob))
@ -138,7 +124,7 @@ cdef class KnowledgeBase:
alias_entry = self._aliases_table[alias_index]
return [Candidate(kb=self,
entity_id_hash=self._entries[entry_index].entity_id_hash,
entity_hash=self._entries[entry_index].entity_hash,
alias_hash=alias_hash,
prior_prob=prob)
for (entry_index, prob) in zip(alias_entry.entry_indices, alias_entry.probs)

2
spacy/pipeline/pipes.pyx
View File

@ -1096,7 +1096,7 @@ class EntityLinker(Pipe):
if candidates:
best_candidate = max(candidates, key=lambda c: c.prior_prob)
for token in ent:
token.ent_kb_id_ = best_candidate.entity_id_
token.ent_kb_id_ = best_candidate.entity_
def get_loss(self, docs, golds, scores):
# TODO

30
spacy/tests/pipeline/test_el.py
View File

@ -17,9 +17,9 @@ def test_kb_valid_entities(nlp):
mykb = KnowledgeBase(nlp.vocab)
# adding entities
mykb.add_entity(entity_id=u'Q1', prob=0.9)
mykb.add_entity(entity_id=u'Q2', prob=0.2)
mykb.add_entity(entity_id=u'Q3', prob=0.5)
mykb.add_entity(entity=u'Q1', prob=0.9)
mykb.add_entity(entity=u'Q2')
mykb.add_entity(entity=u'Q3', prob=0.5)
# adding aliases
mykb.add_alias(alias=u'douglas', entities=[u'Q2', u'Q3'], probabilities=[0.8, 0.2])
@ -35,9 +35,9 @@ def test_kb_invalid_entities(nlp):
mykb = KnowledgeBase(nlp.vocab)
# adding entities
mykb.add_entity(entity_id=u'Q1', prob=0.9)
mykb.add_entity(entity_id=u'Q2', prob=0.2)
mykb.add_entity(entity_id=u'Q3', prob=0.5)
mykb.add_entity(entity=u'Q1', prob=0.9)
mykb.add_entity(entity=u'Q2', prob=0.2)
mykb.add_entity(entity=u'Q3', prob=0.5)
# adding aliases - should fail because one of the given IDs is not valid
with pytest.raises(ValueError):
@ -49,9 +49,9 @@ def test_kb_invalid_probabilities(nlp):
mykb = KnowledgeBase(nlp.vocab)
# adding entities
mykb.add_entity(entity_id=u'Q1', prob=0.9)
mykb.add_entity(entity_id=u'Q2', prob=0.2)
mykb.add_entity(entity_id=u'Q3', prob=0.5)
mykb.add_entity(entity=u'Q1', prob=0.9)
mykb.add_entity(entity=u'Q2', prob=0.2)
mykb.add_entity(entity=u'Q3', prob=0.5)
# adding aliases - should fail because the sum of the probabilities exceeds 1
with pytest.raises(ValueError):
@ -63,9 +63,9 @@ def test_kb_invalid_combination(nlp):
mykb = KnowledgeBase(nlp.vocab)
# adding entities
mykb.add_entity(entity_id=u'Q1', prob=0.9)
mykb.add_entity(entity_id=u'Q2', prob=0.2)
mykb.add_entity(entity_id=u'Q3', prob=0.5)
mykb.add_entity(entity=u'Q1', prob=0.9)
mykb.add_entity(entity=u'Q2', prob=0.2)
mykb.add_entity(entity=u'Q3', prob=0.5)
# adding aliases - should fail because the entities and probabilities vectors are not of equal length
with pytest.raises(ValueError):
@ -77,9 +77,9 @@ def test_candidate_generation(nlp):
mykb = KnowledgeBase(nlp.vocab)
# adding entities
mykb.add_entity(entity_id=u'Q1', prob=0.9)
mykb.add_entity(entity_id=u'Q2', prob=0.2)
mykb.add_entity(entity_id=u'Q3', prob=0.5)
mykb.add_entity(entity=u'Q1', prob=0.9)
mykb.add_entity(entity=u'Q2', prob=0.2)
mykb.add_entity(entity=u'Q3', prob=0.5)
# adding aliases
mykb.add_alias(alias=u'douglas', entities=[u'Q2', u'Q3'], probabilities=[0.8, 0.2])