Metadata-Version: 2.1
Name: vngrs-nlp
Version: 0.1.2.4
Summary: NLP Tools for Turkish Language.
Author: Meliksah Turker
Author-email: turkermeliksah@hotmail.com
License: GNU Affero General Public License v3.0
Project-URL: Documentation, https://vnlp.readthedocs.io/en/latest/
Project-URL: Repository, https://github.com/vngrs-ai/vnlp
Project-URL: Website, https://vnlp.io
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
Provides-Extra: extras
License-File: LICENSE

# <img src="https://github.com/vngrs-ai/vnlp/blob/main/img/logo.png?raw=true" width="256">

## VNLP: Turkish NLP Tools
State of the art, lightweight NLP tools for Turkish language.
Developed by VNGRS.
https://vngrs.com/

### Functionality:
- Sentence Splitter
- Normalizer
	- Spelling/Typo correction
	- Convert numbers to word form
	- Deasciification
- Stopword Remover:
	- Static
	- Dynamic
- Stemmer: Morphological Analyzer & Disambiguator
- Named Entity Recognizer (NER) 
- Dependency Parser
- Part of Speech (POS) Tagger
- Sentiment Analyzer
- Turkish Word Embeddings
	- FastText
	- Word2Vec
- Text Summarization: In development progress...

### Installation
```
pip install vngrs-nlp
```
```
conda install vngrs-nlp
```
### Documentation:
- Detailed documentation about usage, classes, functions, datasets and evaluation metrics are available at [Documentation](https://vnlp.readthedocs.io).

### Usage Example:
**Dependency Parser**
```
from vnlp import DependencyParser
dep_parser = DependencyParser()

dep_parser.predict("Onun için yol arkadaşlarımızı titizlikle seçer, kendilerini iyice sınarız.")
[(1, 'Onun', 5, 'obl'),
(2, 'için', 1, 'case'),
(3, 'yol', 1, 'nmod'),
(4, 'arkadaşlarımızı', 5, 'obj'),
(5, 'titizlikle', 6, 'obl'),
(6, 'seçer', 7, 'acl'),
(7, ',', 10, 'punct'),
(8, 'kendilerini', 10, 'obj'),
(9, 'iyice', 8, 'advmod'),
(10, 'sınarız', 0, 'root'),
(11, '.', 10, 'punct')]

# Spacy's submodule Displacy can be used to visualize DependencyParser result.
import spacy
from vnlp import DependencyParser
dependency_parser = DependencyParser()
result = dependency_parser.predict("Oğuz'un kırmızı bir Astra'sı vardı.", displacy_format = True)
spacy.displacy.render(result, style="dep", manual = True)
```
# <img src="https://raw.githubusercontent.com/vngrs-ai/vnlp/main/img/dp_vis_sample.png" width="512">

