Classification dataset generator library for high level Nlp tasks
Project description
Data Generator
Video Lectures
For Developers
You can also see Cython, Java, Swift, Js, C++, or C# repository.
Requirements
Python
To check if you have a compatible version of Python installed, use the following command:
python -V
You can find the latest version of Python here.
Git
Install the latest version of Git.
Pip Install
pip3 install NlpToolkit-DataGenerator
Download Code
In order to work on code, create a fork from GitHub page. Use Git for cloning the code to your local or below line for Ubuntu:
git clone <your-fork-git-link>
A directory called DataGenerator will be created. Or you can use below link for exploring the code:
git clone https://github.com/starlangsoftware/DataGenerator-Py.git
Open project with Pycharm IDE
Steps for opening the cloned project:
- Start IDE
- Select File | Open from main menu
- Choose
DataGenerator-PY
file - Select open as project option
- Couple of seconds, dependencies will be downloaded.
Detailed Description
AnnotatedDataSetGenerator
DataSet yaratmak için AnnotatedDataSetGenerator sınıfı önce üretilir.
AnnotatedDataSetGenerator(self, folder: str, pattern: str, instanceGenerator: InstanceGenerator)
Ardından generate metodu ile DataSet yaratılır.
generate(self) -> DataSet
InstanceGenerator
DataGeneratorlerin InstanceGeneratorlere ihtiyacı vardır. Bunlar bir tek kelimeden bir Instance yaratan sınıflardır.
generateInstanceFromSentence(self, sentence: Sentence, wordIndex: int) -> Instance
NER problemi için NerInstanceGenerator, FeaturedNerInstanceGenerator ve VectorizedNerInstanceGeneratorsınıfı
ShallowParse problemi için ShallowParseInstanceGenerator, FeaturedShallowParseInstanceGenerator ve VectorizedShallowParseInstanceGenerator sınıfı
WSD problemi için SemanticInstanceGenerator, FeaturedSemanticInstanceGenerator ve VectorizedSemanticInstanceGenerator sınıfı
Morphological Disambiguation problemi için FeaturedDisambiguationInstanceGenerator sınıfı
Example Generated DataSet
Word Sense Disambiguation Task
The following Table shows the sample text represented with sense labels and three possible features, namely the root form of the word, the part of speech (POS) tag of the word, and a boolean feature for checking the capital case.
Word | Root | Pos | Capital | ... | Tag |
---|---|---|---|---|---|
Yüzündeki | yüz | Noun | True | ... | yüz3 |
ketçap | ketçap | Noun | False | ... | ketçap1 |
lekesi | leke | Noun | False | ... | leke2 |
yüzdükten | yüz | Verb | False | ... | yüz2 |
sonra | sonra | PCAbl | False | ... | sonra1 |
çıkmış | çık | Verb | False | ... | çık10 |
. | . | Punctuation | False | ... | .1 |
Named Entity Recognition Task
The following Table shows the sample text represented with tag labels and three possible features, namely the root form of the word, the part of speech (POS) tag of the word, and a boolean feature for checking the capital case.
Word | Root | Pos | Capital | ... | Tag |
---|---|---|---|---|---|
Türk | Türk | Noun | True | ... | ORGANIZATION |
Hava | Hava | Noun | True | ... | ORGANIZATION |
Yolları | Yol | Noun | True | ... | ORGANIZATION |
bu | bu | Pronoun | False | ... | NONE |
Pazartesi'den | Pazartesi | Noun | True | ... | TIME |
itibaren | itibaren | Adverb | False | ... | NONE |
İstanbul | İstanbul | Noun | True | ... | LOCATION |
Ankara | Ankara | Noun | True | ... | LOCATION |
güzergahı | güzergah | Noun | False | ... | NONE |
için | için | Adverb | False | ... | NONE |
indirimli | indirimli | Adjective | False | ... | NONE |
satışlarını | sat | Noun | False | ... | NONE |
90 | 90 | Number | False | ... | MONEY |
TL'den | TL | Noun | True | ... | MONEY |
başlatacağını | başlat | Noun | False | ... | NONE |
açıkladı | açıkla | Verb | False | ... | NONE |
. | . | Punctuation | False | ... | NONE |
Shallow Parse Task
The following Table shows the sample text represented with chunk labels and three possible features, namely the root form of the word, the part of speech (POS) tag of the word, and a boolean feature for checking the capital case.
Word | Root | Pos | Capital | ... | Tag |
---|---|---|---|---|---|
Türk | Türk | Noun | True | ... | ÖZNE |
Hava | Hava | Noun | True | ... | ÖZNE |
Yolları | yol | Noun | True | ... | ÖZNE |
Salı | Salı | Noun | True | ... | ZARF TÜMLECİ |
günü | gün | Noun | False | ... | ZARF TÜMLECİ |
yeni | yeni | Adjective | False | ... | NESNE |
indirimli | indirimli | Adjective | False | ... | NESNE |
fiyatlarını | fiyat | Noun | False | ... | NESNE |
açıkladı | açıkla | Verb | False | ... | YÜKLEM |
. | . | Punctuation | False | ... | HİÇBİRİ |
Cite
If you use this resource on your research, please cite the following paper:
@article{acikgoz,
title={All-words word sense disambiguation for {T}urkish},
author={O. Açıkg{\"o}z and A. T. G{\"u}rkan and B. Ertopçu and O. Topsakal and B. {\"O}zenç and A. B. Kanburoğlu and {\.{I}}. Çam and B. Avar and G. Ercan and O. T. Y{\i}ld{\i}z},
journal={2017 International Conference on Computer Science and Engineering (UBMK)},
year={2017},
pages={490-495}
}
@inproceedings{ertopcu17,
author={B. {Ertopçu} and A. B. {Kanburoğlu} and O. {Topsakal} and O. {Açıkgöz} and A. T. {Gürkan} and B. {Özenç} and İ. {Çam} and B. {Avar} and G. {Ercan} and O. T. {Yıldız}},
booktitle={2017 International Conference on Computer Science and Engineering (UBMK)}, title={A new approach for named entity recognition},
year={2017},
pages={474-479}
}
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