KnowledgeBase
The KnowledgeBase object is an abstract class providing a method to generate
Candidate objects, which are plausible external
identifiers given a certain textual mention. Each such Candidate holds
information from the relevant KB entities, such as its frequency in text and
possible aliases. Each entity in the knowledge base also has a pretrained entity
vector of a fixed size.
Beyond that, KnowledgeBase classes have to implement a number of utility
functions called by the EntityLinker component.
KnowledgeBase.__init__ method
KnowledgeBase is an abstract class and cannot be instantiated. Its child
classes should call __init__() to set up some necessary attributes.
| Name | Description |
|---|---|
vocab | The shared vocabulary. Vocab |
entity_vector_length | Length of the fixed-size entity vectors. int |
KnowledgeBase.entity_vector_length property
The length of the fixed-size entity vectors in the knowledge base.
| Name | Description |
|---|---|
| RETURNS | Length of the fixed-size entity vectors. int |
KnowledgeBase.get_candidates method
Given a certain textual mention as input, retrieve a list of candidate entities
of type Candidate.
| Name | Description |
|---|---|
mention | The textual mention or alias. Span |
| RETURNS | An iterable of relevant Candidate objects. Iterable[Candidate] |
KnowledgeBase.get_candidates_batch method
Same as get_candidates(), but for an arbitrary
number of mentions. The EntityLinker component will call
get_candidates_batch() instead of get_candidates(), if the config parameter
candidates_batch_size is greater or equal than 1.
The default implementation of get_candidates_batch() executes
get_candidates() in a loop. We recommend implementing a more efficient way to
retrieve candidates for multiple mentions at once, if performance is of concern
to you.
| Name | Description |
|---|---|
mentions | The textual mention or alias. Iterable[Span] |
| RETURNS | An iterable of iterable with relevant Candidate objects. Iterable[Iterable[Candidate]] |
KnowledgeBase.get_alias_candidates method
From spaCy 3.5 on KnowledgeBase is an abstract class (with
InMemoryLookupKB being a drop-in replacement) to
allow more flexibility in customizing knowledge bases. Some of its methods were
moved to InMemoryLookupKB during this refactoring,
one of those being get_alias_candidates(). This method is now available as
InMemoryLookupKB.get_alias_candidates().
Note:
InMemoryLookupKB.get_candidates()
defaults to
InMemoryLookupKB.get_alias_candidates().
KnowledgeBase.get_vector method
Given a certain entity ID, retrieve its pretrained entity vector.
| Name | Description |
|---|---|
entity | The entity ID. str |
| RETURNS | The entity vector. Iterable[float] |
KnowledgeBase.get_vectors method
Same as get_vector(), but for an arbitrary number of
entity IDs.
The default implementation of get_vectors() executes get_vector() in a loop.
We recommend implementing a more efficient way to retrieve vectors for multiple
entities at once, if performance is of concern to you.
| Name | Description |
|---|---|
entities | The entity IDs. Iterable[str] |
| RETURNS | The entity vectors. Iterable[Iterable[numpy.ndarray]] |
KnowledgeBase.to_disk method
Save the current state of the knowledge base to a directory.
| Name | Description |
|---|---|
path | A path to a directory, which will be created if it doesn’t exist. Paths may be either strings or Path-like objects. Union[str,Path] |
exclude | List of components to exclude. Iterable[str] |
KnowledgeBase.from_disk method
Restore the state of the knowledge base from a given directory. Note that the
Vocab should also be the same as the one used to create the KB.
| Name | Description |
|---|---|
loc | A path to a directory. Paths may be either strings or Path-like objects. Union[str,Path] |
exclude | List of components to exclude. Iterable[str] |
| RETURNS | The modified KnowledgeBase object. KnowledgeBase |
Candidate class
A Candidate object refers to a textual mention (alias) that may or may not be
resolved to a specific entity from a KnowledgeBase. This will be used as input
for the entity linking algorithm which will disambiguate the various candidates
to the correct one. Each candidate (alias, entity) pair is assigned to a
certain prior probability.
Candidate.__init__ method
Construct a Candidate object. Usually this constructor is not called directly,
but instead these objects are returned by the get_candidates method of the
entity_linker pipe.
| Name | Description |
|---|---|
kb | The knowledge base that defined this candidate. KnowledgeBase |
entity_hash | The hash of the entity’s KB ID. int |
entity_freq | The entity frequency as recorded in the KB. float |
alias_hash | The hash of the textual mention or alias. int |
prior_prob | The prior probability of the alias referring to the entity. float |
Candidate attributes
| Name | Description |
|---|---|
entity | The entity’s unique KB identifier. int |
entity_ | The entity’s unique KB identifier. str |
alias | The alias or textual mention. int |
alias_ | The alias or textual mention. str |
prior_prob | The prior probability of the alias referring to the entity. long |
entity_freq | The frequency of the entity in a typical corpus. long |
entity_vector | The pretrained vector of the entity. numpy.ndarray |