
Entity recognition using scikit CRF
Decscription
This is a simple python applicaion that uses sklearn-crfsuite for entity recognition using CRF.
Installation
Install this package using pip by running the follwing command:
pip install scikitcrf_ner
Usage
import the package using:
from scikitcrf_ner import entityRecognition
Train the model using:
entityRecognition.train("path\\to\\trainingfile.json")Refer the sample training file(sample_train.json), the training file should be json formatted
Predict the entities by:
entityRecognition.predict("Utterance")
Sample code
Refer this sample code:
from scikitcrf_ner import entityRecognition as ner
ner.train("sample_train.json")
entities = ner.predict("show me some Indian restaurants")
print(entites)
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for scikitcrf-ner 3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| scikitcrf_ner-3.2.tar.gz | 3.3 kB | Without provenance | Details |
Release files / scikitcrf_ner-3.2.tar.gz
| Download URL | scikitcrf_ner-3.2.tar.gz |
|---|---|
| Size | 3.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3fab7df2063ee6ad3e2233bbd7022efd69062b6d9e162996ce633321c18ee16f
|
|
BLAKE2b-256 checksum How to use checksums |
4c800a48e687e2dc2b0d4b3cbccadfeef5bc163b72c2b0d77047f0f672e8419b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for scikitcrf-ner 3.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
