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update EL API

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svlandeg 2020-08-06 16:40:48 +02:00
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website/docs/api/entitylinker.md
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@ -33,14 +33,14 @@ architectures and their arguments and hyperparameters.
> nlp.add_pipe("entity_linker", config=config) > nlp.add_pipe("entity_linker", config=config)
> ``` > ```
| Setting | Type | Description | Default | | Setting | Type | Description | Default |
| ---------------- | -------------------------------------------------------- | ------------------------------------------------------------------------- | ------------------------------------------------------ | | ---------------- | -------------------------------------------------------- | --------------------------------------------------------------------------- | ------------------------------------------------------ |
| `labels_discard` | `Iterable[str]` | NER labels that will automatically get a "NIL" prediction. | `[]` | | `labels_discard` | `Iterable[str]` | NER labels that will automatically get a "NIL" prediction. | `[]` |
| `incl_prior` | bool | Whether or not to include prior probabilities from the KB in the model. | `True` | | `incl_prior` | bool | Whether or not to include prior probabilities from the KB in the model. | `True` |
| `incl_context` | bool | Whether or not to include the local context in the model. | `True` | | `incl_context` | bool | Whether or not to include the local context in the model. | `True` |
| `model` | [`Model`](https://thinc.ai/docs/api-model) | The model to use. | [EntityLinker](/api/architectures#EntityLinker) | | `model` | [`Model`](https://thinc.ai/docs/api-model) | The model to use. | [EntityLinker](/api/architectures#EntityLinker) |
| `kb_loader` | `Callable[[Vocab], KnowledgeBase]` | Function that creates a [`KnowledgeBase`](/api/kb) from a Vocab instance. | An empty KnowledgeBase with `entity_vector_length` 64. | | `kb_loader` | `Callable[[Vocab], KnowledgeBase]` | Function that creates a [`KnowledgeBase`](/api/kb) from a `Vocab` instance. | An empty KnowledgeBase with `entity_vector_length` 64. |
| `get_candidates` | `Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]` | Function that generates plausible candidates for a given `Span` object. | Built-in dictionary-lookup function. | | `get_candidates` | `Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]` | Function that generates plausible candidates for a given `Span` object. | Built-in dictionary-lookup function. |
```python ```python
https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/entity_linker.py https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/entity_linker.py
@ -55,7 +55,11 @@ https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/entity_linker.py
> entity_linker = nlp.add_pipe("entity_linker") > entity_linker = nlp.add_pipe("entity_linker")
> >
> # Construction via add_pipe with custom model > # Construction via add_pipe with custom model
> config = {"model": {"@architectures": "my_el"}} > config = {"model": {"@architectures": "my_el.v1"}}
> entity_linker = nlp.add_pipe("entity_linker", config=config)
>
> # Construction via add_pipe with custom KB and candidate generation
> config = {"kb_loader": {"@assets": "my_kb.v1"}, "get_candidates": {"@assets": "my_candidates.v1"},}
> entity_linker = nlp.add_pipe("entity_linker", config=config) > entity_linker = nlp.add_pipe("entity_linker", config=config)
> >
> # Construction from class > # Construction from class
@ -67,18 +71,20 @@ Create a new pipeline instance. In your application, you would normally use a
shortcut for this and instantiate the component using its string name and shortcut for this and instantiate the component using its string name and
[`nlp.add_pipe`](/api/language#add_pipe). [`nlp.add_pipe`](/api/language#add_pipe).
<!-- TODO: finish API docs --> Note that both the internal KB as well as the Candidate generator can be
customized by providing custom registered functions.
| Name | Type | Description | | Name | Type | Description |
| ---------------- | --------------- | ------------------------------------------------------------------------------------------- | | ---------------- | -------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| `vocab` | `Vocab` | The shared vocabulary. | | `vocab` | `Vocab` | The shared vocabulary. |
| `model` | `Model` | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. | | `model` | `Model` | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. |
| `name` | str | String name of the component instance. Used to add entries to the `losses` during training. | | `name` | str | String name of the component instance. Used to add entries to the `losses` during training. |
| _keyword-only_ | | | | _keyword-only_ | | |
| `kb` | `KnowlegeBase` | The [`KnowledgeBase`](/api/kb) holding all entities and their aliases. | | `kb_loader` | `Callable[[Vocab], KnowledgeBase]` | Function that creates a [`KnowledgeBase`](/api/kb) from a `Vocab` instance. |
| `labels_discard` | `Iterable[str]` | NER labels that will automatically get a "NIL" prediction. | | `get_candidates` | `Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]` | Function that generates plausible candidates for a given `Span` object. |
| `incl_prior` | bool | Whether or not to include prior probabilities from the KB in the model. | | `labels_discard` | `Iterable[str]` | NER labels that will automatically get a "NIL" prediction. |
| `incl_context` | bool | Whether or not to include the local context in the model. | | `incl_prior` | bool | Whether or not to include prior probabilities from the KB in the model. |
| `incl_context` | bool | Whether or not to include the local context in the model. |
## EntityLinker.\_\_call\_\_ {#call tag="method"} ## EntityLinker.\_\_call\_\_ {#call tag="method"}