Extract phrase from English sentence such as noun, verb, preposition based on NLP task word chunking and HuggingFace library
Project description
Phrase extraction
Input: PennyLane went to the school
Output: [{'Noun Phrase': 'PennyLane'}, {'Verb Phrase': 'went'}, {'Preposition': 'to'}, {'Noun Phrase': 'the school'}]
I train a sequence tagging model based on RoBERTa of Huggingface. The training code is given in train.py.
How to use
from PhrExt import PhraseExtractor
if __name__ == "__main__":
phrase_extractor = PhraseExtractor('transZ/phrext', 'roberta-base')
sent = "PennyLane went to the school"
res = phrase_extractor(sent)
print(res)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
PhrExt-0.1.0.tar.gz
(6.4 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file PhrExt-0.1.0.tar.gz.
File metadata
- Download URL: PhrExt-0.1.0.tar.gz
- Upload date:
- Size: 6.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4295be1b7743e8a99b593306b0e103b1cbbf7531309428b1c025af08916109ce
|
|
| MD5 |
b93f19778e4c557a04dfdb0f722e17bc
|
|
| BLAKE2b-256 |
c69a3a73737133c90bf9d2ece80665e834ba553de13565cb8bb9ce419061766b
|
File details
Details for the file PhrExt-0.1.0-py3-none-any.whl.
File metadata
- Download URL: PhrExt-0.1.0-py3-none-any.whl
- Upload date:
- Size: 7.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b0edeb5b9883c5326da332fdfe9a60a38e26d0acb1e433f19dd1aad57564fcc2
|
|
| MD5 |
c74f1787d4e178868a36ebcc943ed561
|
|
| BLAKE2b-256 |
6b450672b557b4d3947257fcd8f5e23762ba825b2267e0dc35bb2e0acc853477
|