spaCy/website/docs/usage/101/_named-entities.md

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A named entity is a "real-world object" that's assigned a name for example, a
person, a country, a product or a book title. spaCy can **recognize
[various types](/api/annotation#named-entities)** of named entities in a
document, by asking the model for a **prediction**. Because models are
statistical and strongly depend on the examples they were trained on, this
doesn't always work _perfectly_ and might need some tuning later, depending on
your use case.
Named entities are available as the `ents` property of a `Doc`:
```python
### {executable="true"}
import spacy
nlp = spacy.load("en_core_web_sm")
doc = nlp("Apple is looking at buying U.K. startup for $1 billion")
for ent in doc.ents:
print(ent.text, ent.start_char, ent.end_char, ent.label_)
```
> - **Text:** The original entity text.
> - **Start:** Index of start of entity in the `Doc`.
> - **End:** Index of end of entity in the `Doc`.
> - **Label:** Entity label, i.e. type.
| Text | Start | End | Label | Description |
| ----------- | :---: | :-: | ------- | ---------------------------------------------------- |
| Apple | 0 | 5 | `ORG` | Companies, agencies, institutions. |
| U.K. | 27 | 31 | `GPE` | Geopolitical entity, i.e. countries, cities, states. |
| \$1 billion | 44 | 54 | `MONEY` | Monetary values, including unit. |
Using spaCy's built-in [displaCy visualizer](/usage/visualizers), here's what
our example sentence and its named entities look like:
import DisplaCyEntHtml from 'images/displacy-ent1.html'; import { Iframe } from
'components/embed'
<Iframe title="displaCy visualization of entities" html={DisplaCyEntHtml} height={100} />