/Name-Entity-Recognition

Primary LanguagePython

Name-Entity-Recognition

Created two models to slove the Name entity recognition. Name-Entity-Recognition (NER) is a subtask of Natural Language Processing (NLP) that involves identifying and extracting entities such as person names, organizations, locations, and other types of named entities from unstructured text.

  1. General
  2. Program Structure
  3. Installation

General

The goal is to create model that will recogize the right entity of each word in the sentence.

Program Structure

  • model1_318170917_3222995358.py - the first model, SVC
  • model23_318170917_3222995358.py - the second model, fully connected network.
  • generate_comp_tagged.py - uses the model to tag the data.

Network-Structure

The network is fc based network including three layers with the following dimensions

Installation

  1. Open the terminal

  2. Clone the project by:

    $ git clone https://github.com/elaysason/Name-Entity-Recognition.git
  1. Run the generate_comp_tagged.py.py file by:
    $ python generate_comp_tagged.py.py