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Update alias/mention usage in doc(strings).

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This commit is contained in:
Raphael Mitsch 2023-03-14 13:33:05 +01:00
parent be858981e6
commit 28dbed64cb
3 changed files with 20 additions and 20 deletions
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12
spacy/kb/candidate.pyx
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@ -49,7 +49,7 @@ cdef class InMemoryCandidate(Candidate):
self, self,
kb: InMemoryLookupKB, kb: InMemoryLookupKB,
entity_hash: int, entity_hash: int,
mention_hash: int, alias_hash: int,
entity_vector: vector[float], entity_vector: vector[float],
prior_prob: float, prior_prob: float,
entity_freq: float entity_freq: float
@ -59,9 +59,9 @@ cdef class InMemoryCandidate(Candidate):
entity_id (int): Entity ID as hash that can be looked up with InMemoryKB.vocab.strings.__getitem__(). entity_id (int): Entity ID as hash that can be looked up with InMemoryKB.vocab.strings.__getitem__().
entity_freq (int): Entity frequency in KB corpus. entity_freq (int): Entity frequency in KB corpus.
entity_vector (List[float]): Entity embedding. entity_vector (List[float]): Entity embedding.
mention_hash (int): Mention hash. alias_hash (int): Alias hash.
prior_prob (float): Prior probability of entity for this mention. I. e. the probability that, independent of prior_prob (float): Prior probability of entity for this alias. I. e. the probability that, independent of
the context, this mention - which matches one of this entity's aliases - resolves to one this entity. the context, this alias - which matches one of this entity's aliases - resolves to one this entity.
""" """
super().__init__() super().__init__()
@ -69,7 +69,7 @@ cdef class InMemoryCandidate(Candidate):
self._entity_vector = entity_vector self._entity_vector = entity_vector
self._prior_prob = prior_prob self._prior_prob = prior_prob
self._kb = kb self._kb = kb
self._mention = mention_hash self._mention = alias_hash
self._entity_freq = entity_freq self._entity_freq = entity_freq
@property @property
@ -82,7 +82,7 @@ cdef class InMemoryCandidate(Candidate):
@property @property
def prior_prob(self) -> float: def prior_prob(self) -> float:
"""RETURNS (float): Prior probability that this mention, which matches one of this entity's aliases, resolves to """RETURNS (float): Prior probability that this alias, which matches one of this entity's synonyms, resolves to
this entity.""" this entity."""
return self._prior_prob return self._prior_prob

2
spacy/kb/kb_in_memory.pyx
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@ -245,7 +245,7 @@ cdef class InMemoryLookupKB(KnowledgeBase):
InMemoryCandidate( InMemoryCandidate(
kb=self, kb=self,
entity_hash=self._entries[entry_index].entity_hash, entity_hash=self._entries[entry_index].entity_hash,
mention_hash=alias_hash, alias_hash=alias_hash,
entity_vector=self._vectors_table[self._entries[entry_index].vector_index], entity_vector=self._vectors_table[self._entries[entry_index].vector_index],
prior_prob=prior_prob, prior_prob=prior_prob,
entity_freq=self._entries[entry_index].freq entity_freq=self._entries[entry_index].freq

26
website/docs/api/kb.mdx
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@ -175,11 +175,11 @@ Restore the state of the knowledge base from a given directory. Note that the
## InMemoryCandidate {id="candidate",tag="class"} ## InMemoryCandidate {id="candidate",tag="class"}
An `InMemoryCandidate` object refers to a textual mention (alias) that may or may An `InMemoryCandidate` object refers to a textual mention (alias) that may or
not be resolved to a specific entity from a `KnowledgeBase`. This will be used may not be resolved to a specific entity from a `KnowledgeBase`. This will be
as input for the entity linking algorithm which will disambiguate the various used as input for the entity linking algorithm which will disambiguate the
candidates to the correct one. Each candidate `(alias, entity)` pair is assigned various candidates to the correct one. Each candidate `(alias, entity)` pair is
to a certain prior probability. assigned to a certain prior probability.
### InMemoryCandidate.\_\_init\_\_ {id="candidate-init",tag="method"} ### InMemoryCandidate.\_\_init\_\_ {id="candidate-init",tag="method"}
@ -190,19 +190,19 @@ of the [`entity_linker`](/api/entitylinker) pipe.
> #### Example```python > #### Example```python
> >
> from spacy.kb import InMemoryCandidate candidate = InMemoryCandidate(kb, > from spacy.kb import InMemoryCandidate candidate = InMemoryCandidate(kb,
> entity_hash, entity_freq, entity_vector, mention_hash, prior_prob) > entity_hash, entity_freq, entity_vector, alias_hash, prior_prob)
> >
> ``` > ```
> >
> ``` > ```
| Name | Description | | Name | Description |
| -------------- | ------------------------------------------------------------------------- | | ------------- | ------------------------------------------------------------------------- |
| `kb` | The knowledge base that defined this candidate. ~~KnowledgeBase~~ | | `kb` | The knowledge base that defined this candidate. ~~KnowledgeBase~~ |
| `entity_hash` | The hash of the entity's KB ID. ~~int~~ | | `entity_hash` | The hash of the entity's KB ID. ~~int~~ |
| `entity_freq` | The entity frequency as recorded in the KB. ~~float~~ | | `entity_freq` | The entity frequency as recorded in the KB. ~~float~~ |
| `mention_hash` | The hash of the textual mention. ~~int~~ | | `alias_hash` | The hash of the entity alias. ~~int~~ |
| `prior_prob` | The prior probability of the `alias` referring to the `entity`. ~~float~~ | | `prior_prob` | The prior probability of the `alias` referring to the `entity`. ~~float~~ |
## InMemoryCandidate attributes {id="candidate-attributes"} ## InMemoryCandidate attributes {id="candidate-attributes"}