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	Fix entity_id refactoring problems in docstrings.
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				|  | @ -1,14 +1,11 @@ | |||
| # cython: infer_types=True, profile=True | ||||
| 
 | ||||
| from ..typedefs cimport hash_t | ||||
| 
 | ||||
| from .kb cimport KnowledgeBase | ||||
| from .kb_in_memory cimport InMemoryLookupKB | ||||
| from ..errors import Errors | ||||
| 
 | ||||
| cdef class Candidate: | ||||
|     """A `Candidate` object refers to a textual mention that may or may not be resolved | ||||
|     to a specific `entity_id` from a Knowledge Base. This will be used as input for the entity_id linking | ||||
|     to a specific entity from a Knowledge Base. This will be used as input for the entity linking | ||||
|     algorithm which will disambiguate the various candidates to the correct one. | ||||
|     Each candidate (mention, entity_id) pair is assigned a certain prior probability. | ||||
| 
 | ||||
|  | @ -87,7 +84,7 @@ cdef class InMemoryCandidate(Candidate): | |||
|         entity_vector (List[float]): Entity embedding. | ||||
|         mention_hash (int): Mention hash. | ||||
|         prior_prob (float): Prior probability of entity for this mention - i.e. the probability that, independent of | ||||
|             the context, this mention resolves to this entity_id in the corpus used to build the knowledge base. In | ||||
|             the context, this mention resolves to this entity in the corpus used to build the knowledge base. In | ||||
|             cases in which this isn't always possible (e.g.: the corpus to analyse contains mentions that the KB corpus | ||||
|             doesn't) it might be better to eschew this information and always supply the same value. | ||||
|         """ | ||||
|  |  | |||
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