https://github.com/nxgeo/id-svo-extractor
id-svo-extractor: Extract SVO triples from Indonesian text.
https://github.com/nxgeo/id-svo-extractor
artificial-intelligence indonesian-language indonesian-linguistics indonesian-nlp information-extraction knowledge-extraction knowledge-representation natural-language-processing nlp python rdf-triples spacy spacy-stanza stanza text-analysis triple-extraction
Last synced: 4 months ago
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id-svo-extractor: Extract SVO triples from Indonesian text.
- Host: GitHub
- URL: https://github.com/nxgeo/id-svo-extractor
- Owner: nxgeo
- License: apache-2.0
- Created: 2024-09-27T06:21:37.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-27T19:09:17.000Z (over 1 year ago)
- Last Synced: 2025-08-28T06:26:16.221Z (9 months ago)
- Topics: artificial-intelligence, indonesian-language, indonesian-linguistics, indonesian-nlp, information-extraction, knowledge-extraction, knowledge-representation, natural-language-processing, nlp, python, rdf-triples, spacy, spacy-stanza, stanza, text-analysis, triple-extraction
- Language: Python
- Homepage: https://pypi.org/project/id-svo-extractor/
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# id-svo-extractor
**id-svo-extractor** is a heuristic tool designed to extract SVO (Subject-Verb-Object) triples from Indonesian text. It uses Stanza's state-of-the-art Indonesian language pipeline for NLP.
## Requirements
To use **id-svo-extractor**, you will need Python v3.10 or higher and the following Python package:
- [spacy-stanza](https://github.com/explosion/spacy-stanza) v1.0.4
You must also download Stanza's Indonesian models for `tokenize`, `mwt`, `pos`, `lemma`, and `depparse` processors before initializing the pipeline.
## Installation
Install the package directly from PyPI:
```sh
pip install id-svo-extractor
```
## Usage
Here's a basic example to get you started.
```python
from id_svo_extractor import create_pipeline
from id_svo_extractor.utils import collect_svo_triples
from stanza import download
# Download Stanza's Indonesian models for tokenize, mwt, pos, lemma, and depparse processors.
# This step is mandatory before initializing the NLP pipeline.
download("id", processors="tokenize,mwt,pos,lemma,depparse")
# Initialize the NLP pipeline.
nlp = create_pipeline()
doc = nlp("Niko dan Okin mendesain brosur promosi dan mencetak poster iklan.")
for sentence in doc.sents:
# Extracted triples for each sentence are stored in `svo_triples` custom attribute.
print(sentence._.svo_triples)
# Output:
# [ SVOTriple(s=[Niko], v=[mendesain], o=[brosur, promosi]),
# SVOTriple(s=[Okin], v=[mendesain], o=[brosur, promosi]),
# SVOTriple(s=[Niko], v=[mencetak], o=[poster, iklan]),
# SVOTriple(s=[Okin], v=[mencetak], o=[poster, iklan]) ]
print(collect_svo_triples(doc))
# Output:
# [ ('Niko', 'mendesain', 'brosur promosi'),
# ('Okin', 'mendesain', 'brosur promosi'),
# ('Niko', 'mencetak', 'poster iklan'),
# ('Okin', 'mencetak', 'poster iklan') ]
```
## License
This project is licensed under the Apache License 2.0.