# 12.5 Named Entity Recognition with spaCy¶

- NLP can determine what a text is about
- Named entity recognition attempts to locate and categorize items
  - dates, times, quantities, places, people, things, organizations and more
- May also want to check out Textacy
  - Built on spaCy and supports additional NLP tasks

### Install spaCy¶

- spaCy Quickstart guide
- `conda install -c conda-forge spacy`
  - Windows users should run the Anaconda Prompt as an Administrator
- Download spaCy's English (`en`) "model" for prcessing text

  >     ipython -m spacy download en

### Loading the Language Model¶

- spaCy docs recommend the variable name `nlp`.

In [1]:

    import spacy

In [2]:

    nlp = spacy.load('en')

### Creating a spaCy `Doc`¶

- Use the `nlp` object to create a spaCy `Doc` object representing the document to process.

In [3]:

    document = nlp('In 1994, Tim Berners-Lee founded the ' +
        'World Wide Web Consortium (W3C), devoted to ' +
        'developing web technologies')

### Getting the Named Entities¶

- Returns tuple of `Span`s representing the named entities
- `Span`s have many properties
- Display `text` (the entity's text) and `label_` (the kind of entity)

In [4]:

    for entity in document.ents:
        print(f'{entity.text}: {entity.label_}')

    1994: DATE
    Tim Berners-Lee: PERSON
    the World Wide Web Consortium (W3C: ORG

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