Skip to main content

A library for technology entity recognition and recommendation

Project description

Entity Recognition Library

Purpose

The Entity Recognition serves as a library for identifying technological entities within texts and suggesting relevant technologies using advanced NLP techniques.

Installing the Library

Integrate our library into your project by installing it directly from PyPI:

pip install entity-recognition-lib

The required spaCy model (en_core_web_sm) will be automatically downloaded and installed if not already present on your system.

Using the Library

Here's how to use the Entity Recognition library in your Python scripts:

from entity_recognition_lib import EntityRecognizer

recognizer = EntityRecognizer()
texts = ["Your text here"]
results = recognizer.process_texts(texts)
print(results)

Expected Output

The library processes text to identify and categorize technology entities, delivering structured output that includes identified entities and contextual recommendations.

Example output:

[
  {
    "input_text": "Example text with technology entities",
    "predicted_topic_name": "topic_name",
    "extracted_entities": [
      {
        "entity_name": "entity_1",
        "score": 0.9,
        "category": "Category 1"
      },
      {
        "entity_name": "entity_2",
        "score": 0.8,
        "category": "Category 1"
      }
    ],
    "recommendations": [
      {
        "category": "Category 1",
        "recommendation": "entity_1"
      }
    ]
  }
]

For detailed usage examples and code snippets, please refer to the examples directory in the repository. The examples cover various scenarios, including:

  • Basic usage of the library for entity recognition and recommendation generation
  • Advanced features such as result analysis and visualization
  • Integration samples with popular frameworks like Flask and Streamlit

We recommend exploring the examples to understand how to effectively utilize the Entity-Recognition library in your projects.

Contributing

If you consider contributing to the Entity Recognition library, make sure to check out our Contributing Guide and our Development Guide, for more information on how to run and test the project locally. You are welcome to expand the technology entities corpus or add a new feature.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

entity_recognition_lib-0.1.6.tar.gz (16.5 kB view hashes)

Uploaded Source

Built Distribution

entity_recognition_lib-0.1.6-py3-none-any.whl (17.7 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page