taishi-i/awesome-japanese-nlp-multilabel-dataset

Dataset overview

This is a dataset for Japanese natural language processing with multi-label annotations of research field labels in the NLP domain.

Problem Setting:

• Training Data: GitHub repositories from before 2022
• Test Data: GitHub repositories from 2023
• Objective: To predict multi-labels of research field labels in the NLP domain

Data Collection:

• We used the positive examples from awesome-japanese-nlp-classification-dataset.

Dataset Features:

• A multimodal dataset including GitHub summaries, README files, PDF files, and screenshot images.
• The annotation labels were assigned with reference to Exploring-NLP-Research.

If you need image data and PDF files, please submit a request to the community. This dataset uses text extracted from PDF files and does not include image data.

Based on GitHub's terms of service, please use this dataset for research purposes only.

How to use this dataset

How to load in Python.

from datasets import load_dataset

dataset = load_dataset("taishi-i/awesome-japanese-nlp-multilabel-dataset")

Details of the dataset.

DatasetDict({
    train: Dataset({
        features: ['is_exist', 'url', 'created_at', 'description', 'pdf_text', 'readme_text', 'nlp_taxonomy_classifier_labels', 'awesome_japanese_nlp_labels'],
        num_rows: 407
    })
    validation: Dataset({
        features: ['is_exist', 'url', 'created_at', 'description', 'pdf_text', 'readme_text', 'nlp_taxonomy_classifier_labels', 'awesome_japanese_nlp_labels'],
        num_rows: 17
    })
    test: Dataset({
        features: ['is_exist', 'url', 'created_at', 'description', 'pdf_text', 'readme_text', 'nlp_taxonomy_classifier_labels', 'awesome_japanese_nlp_labels'],
        num_rows: 60
    })
})

Here is a sample of the dataset.

{
  "is_exist": True,
  "url": "https://github.com/scriptin/jmdict-simplified",
  "created_at": "2016-02-07T16:34:32Z",
  "description": "JMdict and JMnedict in JSON format",
  "pdf_text": "scriptin / jmdict-simplified\nPublic\nBranches\nTags\n",
  "readme_text": "# jmdict-simplified\n\n**[JMdict][], [JMnedict][], [Kanjidic][], and [Kradfile/Radkfile][Kradfile] in JSON format**<br>\n",
  "nlp_taxonomy_classifier_labels": [
    "Multilinguality"
  ],
  "awesome_japanese_nlp_labels": [
    "Annotation and Dataset Development",
    "Vocabulary, Dictionary, and Language Input Method"
  ]
}

Baseline

The baseline model was used for TimSchopf/nlp_taxonomy_classifier.

The fine-tuned model was trained using this dataset to fine-tune the baseline model.

Classification Method	Model	Description	Dev Prec.	Dev Rec.	Dev F1	Eval Prec.	Eval Rec.	Eval F1
Random Prediction	-	-	0.034	0.455	0.064	0.042	0.513	0.078
Baseline	TimSchopf/nlp_taxonomy_classifier	✓	0.538	0.382	0.447	0.360	0.354	0.349
Fine-Tuning	TimSchopf/nlp_taxonomy_classifier	✓	0.538	0.509	0.523	0.436	0.484	0.521
Zero-Shot	gpt-4o-2024-08-06	✓	0.560	0.255	0.350	0.476	0.184	0.265

License

We collect and publish this dataset under GitHub Acceptable Use Policies - 7. Information Usage Restrictions and GitHub Terms of Service - H. API Terms for research purposes. This dataset should be used solely for research verification purposes. Adhering to GitHub's regulations is mandatory.