ner-d 0.1

Python module for Named Entity Recognition (NER).

ner-d

ner-d is a Python module for Named Entity Recognition (NER). Named entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify named entity mentions in unstructured text into pre-defined categories such as the person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.

Gives you easy use with a single main function and flexibility for selecting language models. It automatically downloads models if not downloaded before and links on system and finds the entities from given text block.

Prerequisites

• A single dependency listed on requirements.txt and will be installed when you install with pip.

Installation

• Install module using pip:

  $ pip install ner-d

• Download the latest ner-d library from: https://github.com/verifid/ner-d and install module using pip:

  $ pip install -e .

• Extract the source distribution and run:

  $ python setup.py build
  $ python setup.py install

Usage

• ner:

from nerd import ner

doc = ner.name('GitHub launched April 10, 2008, a subsidiary of Microsoft, is an American web-based hosting service for version control using Git.
                It is mostly used for computer code. It offers all of the distributed version control and source code management (SCM) functionality
                of Git as well as adding its own features.', language='en_core_web_sm')
text_label = [(X.text, X.label_) for X in doc]
print(text_label)
// [(u'GitHub', u'ORG'), (u'April 10, 2008', u'DATE'), (u'Microsoft', u'ORG'), (u'American', u'NORP'), (u'Git', u'PERSON'), (u'SCM', u'ORG'), (u'Git', u'PERSON')]