Metadata-Version: 2.1
Name: entity-classification
Version: 0.1.3
Summary: Perform Intent Classification using a list of Entities
Home-page: https://github.com/craigtrim/entity-classification
License: MIT
Keywords: nlp,nlu,ai,classification,intents
Author: Craig Trim
Author-email: craigtrim@gmail.com
Maintainer: Craig Trim
Maintainer-email: craigtrim@gmail.com
Requires-Python: >=3.8.5,<4.0.0
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: baseblock
Project-URL: Repository, https://github.com/craigtrim/entity-classification
Description-Content-Type: text/markdown

# entity-classification

Perform Entity Classification via two inputs: `entity_names: list` and `input_tokens: list`

Assume you wish to classify `network_topology` and you have these tokens extracted from your text:
```python
[
    'edge',
    'network',
    'moderate',
    'cat5',
    'topology',
    'locate'
]
```

Use this code
```python
from entity_classification import classify

classify(entity_names=['network_topology'], input_tokens=input_tokens)
```

The result will be
```python
{
    'result': ['network_topology'],
    'tokens': ['network', 'topology']
}
```

