mirror of
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154 lines
5.1 KiB
Cython
154 lines
5.1 KiB
Cython
# cython: profile=True
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# coding: utf8
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from spacy.errors import user_warning
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cdef class Entity:
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def __init__(self, KnowledgeBase kb, entity_hash, confidence):
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self.kb = kb
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self.entity_hash = entity_hash
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self.confidence = confidence
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property kb_id_:
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"""RETURNS (unicode): ID of this entity in the KB"""
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def __get__(self):
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return self.kb.strings[self.entity_hash]
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property kb_id:
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"""RETURNS (uint64): hash of the entity's KB ID"""
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def __get__(self):
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return self.entity_hash
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property confidence:
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def __get__(self):
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return self.confidence
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cdef class Candidate:
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def __init__(self, KnowledgeBase kb, entity_hash, alias_hash, prior_prob):
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self.kb = kb
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self.entity_hash = entity_hash
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self.alias_hash = alias_hash
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self.prior_prob = prior_prob
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property kb_id_:
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"""RETURNS (unicode): ID of this entity in the KB"""
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def __get__(self):
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return self.kb.strings[self.entity_hash]
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property kb_id:
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"""RETURNS (uint64): hash of the entity's KB ID"""
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def __get__(self):
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return self.entity_hash
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property alias_:
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"""RETURNS (unicode): ID of the original alias"""
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def __get__(self):
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return self.kb.strings[self.alias_hash]
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property alias:
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"""RETURNS (uint64): hash of the alias"""
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def __get__(self):
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return self.alias_hash
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property prior_prob:
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def __get__(self):
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return self.prior_prob
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cdef class KnowledgeBase:
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def __init__(self):
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self._entry_index = PreshMap()
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self._alias_index = PreshMap()
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self.mem = Pool()
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self.strings = StringStore()
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self.create_empty_vectors()
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def __len__(self):
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return self.get_size_entities()
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def get_size_entities(self):
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return self._entries.size() - 1 # not counting dummy element on index 0
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def get_size_aliases(self):
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return self._aliases_table.size() - 1 # not counting dummy element on index 0
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def add_entity(self, unicode entity_id, float prob, vectors=None, features=None):
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"""
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Add an entity to the KB.
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Return the hash of the entity ID at the end
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"""
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cdef hash_t id_hash = self.strings.add(entity_id)
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# Return if this entity was added before
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if id_hash in self._entry_index:
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user_warning("Entity " + entity_id + " already exists in the KB")
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return
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cdef int32_t dummy_value = 342
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self.c_add_entity(entity_hash=id_hash, prob=prob, vector_rows=&dummy_value, feats_row=dummy_value)
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# TODO self._vectors_table.get_pointer(vectors),
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# self._features_table.get(features))
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return id_hash
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def add_alias(self, unicode alias, entities, probabilities):
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"""
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For a given alias, add its potential entities and prior probabilies to the KB.
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Return the alias_hash at the end
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"""
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# Throw an error if the length of entities and probabilities are not the same
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if not len(entities) == len(probabilities):
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raise ValueError("The vectors for entities and probabilities for alias '" + alias
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+ "' should have equal length, but found "
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+ str(len(entities)) + " and " + str(len(probabilities)) + "respectively.")
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# Throw an error if the probabilities sum up to more than 1
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prob_sum = sum(probabilities)
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if prob_sum > 1:
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raise ValueError("The sum of prior probabilities for alias '" + alias + "' should not exceed 1, "
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+ "but found " + str(prob_sum))
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cdef hash_t alias_hash = self.strings.add(alias)
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# Return if this alias was added before
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if alias_hash in self._alias_index:
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user_warning("Alias " + alias + " already exists in the KB")
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return
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cdef hash_t entity_hash
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cdef vector[int64_t] entry_indices
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cdef vector[float] probs
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for entity, prob in zip(entities, probabilities):
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entity_hash = self.strings[entity]
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if not entity_hash in self._entry_index:
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raise ValueError("Alias '" + alias + "' defined for unknown entity '" + entity + "'")
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entry_index = <int64_t>self._entry_index.get(entity_hash)
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entry_indices.push_back(int(entry_index))
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probs.push_back(float(prob))
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self.c_add_aliases(alias_hash=alias_hash, entry_indices=entry_indices, probs=probs)
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return alias_hash
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def get_candidates(self, unicode alias):
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cdef hash_t alias_hash = self.strings[alias]
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alias_index = <int64_t>self._alias_index.get(alias_hash)
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alias_entry = self._aliases_table[alias_index]
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return [Candidate(kb=self,
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entity_hash=self._entries[entry_index].entity_hash,
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alias_hash=alias_hash,
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prior_prob=prob)
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for (entry_index, prob) in zip(alias_entry.entry_indices, alias_entry.probs)]
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