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Add API docs

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Adriane Boyd 2020-09-24 12:51:16 +02:00
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@ -219,6 +219,30 @@ alignment mode `"strict".
| `alignment_mode` | How character indices snap to token boundaries. Options: `"strict"` (no snapping), `"contract"` (span of all tokens completely within the character span), `"expand"` (span of all tokens at least partially covered by the character span). Defaults to `"strict"`. ~~str~~ | | `alignment_mode` | How character indices snap to token boundaries. Options: `"strict"` (no snapping), `"contract"` (span of all tokens completely within the character span), `"expand"` (span of all tokens at least partially covered by the character span). Defaults to `"strict"`. ~~str~~ |
| **RETURNS** | The newly constructed object or `None`. ~~Optional[Span]~~ | | **RETURNS** | The newly constructed object or `None`. ~~Optional[Span]~~ |
## Doc.set_ents {#ents tag="method" new="3"}
Set the named entities in the document.
> #### Example
>
> ```python
> from spacy.tokens import Span
> doc = nlp("Mr. Best flew to New York on Saturday morning.")
> doc.set_ents([Span(doc, 0, 2, "PERSON")])
> ents = list(doc.ents)
> assert ents[0].label_ == "PERSON"
> assert ents[0].text == "Mr. Best"
> ```
| Name | Description |
| -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| entities | Spans with labels to set as entities. ~~List[Span]~~ |
| _keyword-only_ | |
| blocked | Spans to set as "blocked" (never an entity) for spacy's built-in NER component. Other components may ignore this setting. ~~Optional[List[Span]]~~ |
| missing | Spans with missing/unknown entity information. ~~Optional[List[Span]]~~ |
| outside | Spans outside of entities (O in IOB). ~~Optional[List[Span]]~~ |
| default | How to set entity annotation for tokens outside of any provided spans. Options: "blocked", "missing", "outside" and "unmodified" (preserve current state). Defaults to "outside". ~~str~~ |
## Doc.similarity {#similarity tag="method" model="vectors"} ## Doc.similarity {#similarity tag="method" model="vectors"}
Make a semantic similarity estimate. The default estimate is cosine similarity Make a semantic similarity estimate. The default estimate is cosine similarity
@ -542,7 +566,6 @@ objects, if the entity recognizer has been applied.
> ```python > ```python
> doc = nlp("Mr. Best flew to New York on Saturday morning.") > doc = nlp("Mr. Best flew to New York on Saturday morning.")
> ents = list(doc.ents) > ents = list(doc.ents)
> assert ents[0].label == 346
> assert ents[0].label_ == "PERSON" > assert ents[0].label_ == "PERSON"
> assert ents[0].text == "Mr. Best" > assert ents[0].text == "Mr. Best"
> ``` > ```