Datasets:

Deddy
/

Indonesia-dataset-2023

@@ -1,175 +1,198 @@
 ---
 license: mit
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-# Indonesian Dataset
-Collections of Indonesian Natural Language Processing dictionaries, corpus, datasets.
-## Table of contents
-  * [Crawl](#crawl)
-    * [Kaskus WebText](#kaskus-webtext)
-    * [Twitter Puisi](#twitter-puisi)
-    * [Wipedia Links](#wikipedia-links)
-  * [Dictionary](#dictionary)
-    * [KBBI](#kbbi)
-    * [Wordlist](#wordlist)
-  * [Dump](#dump)
-    * [CC-News-ID](#cc-news-id)
-    * [Javanese Text](#javanese-text)
-    * [mC4](#mc4)
-    * [Twitter](#twitter)
-  * [Multimodal](#multimodal)
-      * [CC3M](#cc3m)
-      * [CC12M](#cc12m)
-      * [YFCC100M OpenAI Subset](#yfcc100m-openai-subset)
-  * [Paraphrase](#paraphrase)
-    * [MultiNLI](#multinli)
-    * [ParaBank](#parabank)
-    * [ParaNMT](#paranmt)
-    * [PAWS](#paws)
-    * [SBERT Paraphrase Data](#sbert-paraphrase-data)
-    * [SNLI](#snli)
-  * [Question Answering](#question-answering)
-    * [SQuAD](#squad)
-    * [Mathematics Dataset](#mathematics-dataset)
-  * [Speech](#speech)
-    * [Google TTS](#google-tts)
-    * [Unsupervised](#unsupervised)
-  * [Summarization](#summarization)
-    * [Gigaword](#gigaword)
-    * [Reddit TLDR](#reddit-tldr)
-    * [WikiHow](#wikihow)
-  * [Translation](#translation)
-    * [Europarl](#europarl)
-    * [EuroPat](#europat)
-    * [ParaCrawl](#paracrawl)
-## [Crawl](crawl)
-#### [Kaskus WebText](crawl/kaskus-webtext)
-Scraped content from Kaskus with 3 cendol or more.
-#### [Twitter Puisi](crawl/twitter-puisi)
-Poems from various user on Twitter.
-#### [Wikipedia Links](crawl/wikipedia-links)
-Scraped content from Wikipedia external links.
-## [Dictionary](dictionary)
-#### [KBBI](https://github.com/IllegalStashes/kbbi)
-Scraped Kamus Besar Bahasa Indonesia Daring.
-#### [Wordlist](dictionary/wordlist)
-105,226 words from Kamus Besar Bahasa Indonesia.
-## [Dump](dump)
-#### [CC-News-ID](dump/cc-news)
-Processed CC-News (CommonCrawl News). Contains News from 2016-2021 from various news outlets.
-#### [Javanese Text](dump/jv-text)
-Extracting Javanese text from available data.
-#### [mC4](dump/mc4)
-(Hopefully) clean mC4.
-#### [Twitter](dump/twitter)
-Twitter dump from [ArchiveTeam Twitter Stream Grab](https://archive.org/details/twitterstream). More data will be released soon!
-## [Multimodal](multimodal)
-#### [CC3M](multimodal/cc3m)
-Translated Conceptual Captions 3M from Google Research.
-#### [CC12M](multimodal/cc12m)
-Translated Conceptual Captions 12M from Google Research, meant to be used for vision-and-language pre-training.
-#### [YFCC100M OpenAI Subset](multimodal/yfcc100m_openai)
-Translated YFCC100M OpenAI Subset used in CLIP dataset ablation.
-## [Paraphrase](paraphrase)
-#### [MultiNLI](paraphrase/multinli)
-Translated Multi-Genre Natural Language Inference (MultiNLI). The corpus is modeled on the SNLI corpus, but differs in that covers a range of genres of spoken and written text.
-#### [ParaBank](paraphrase/parabank)
-Translated ParaBank v2.0 dataset.
-#### [ParaNMT](paraphrase/paranmt)
-Translated ParaNMT dataset, 5M filtered variant.
-#### [PAWS](paraphrase/paws)
-Translated [PAWS](https://github.com/google-research-datasets/paws) dataset from Google Research.
-#### [SBERT Paraphrase Data](paraphrase/sbert)
-Various paraphrase datasets compiled by [SBERT](https://www.sbert.net/examples/training/paraphrases/README.html) translated to Indonesian.
-#### [SNLI](paraphrase/snli)
-The Stanford Natural Language Inference (SNLI) corpus, translated to Indonesian.
-## [Question Answering](question-answering)
-#### [SQuAD](question-answering/squad)
-Translated SQuAD from Stanford University.
-#### [Mathematics Dataset](question-answering/mathematics_dataset)
-Automatically generated mathematical question and answer pairs. Translated from DeepMind's Mathematics Dataset.
-## [Speech](speech)
-#### [Google TTS](speech/gtts)
-Automatically generated speech using Google Translate TTS (id-ID-Wavenet-A).
-#### [Unsupervised](speech/unsupervised)
-A large-scale Indonesian speech corpus for pre-training speech recognition model.
-## [Summarization](summarization)
-#### [Gigaword](summarization/gigaword)
-Translated English Gigaword dataset.
-#### [Reddit TLDR](summarization/reddit_tldr)
-4 Million content-summary pairs translated from Webis-TLDR-17.
-#### [WikiHow](summarization/wikihow)
-Replicate [WikiHow: A Large Scale Text Summarization Dataset](https://arxiv.org/abs/1810.09305) to Indonesian.
-## [Translation](translation)
-#### [Europarl](translation/europarl)
-A parallel corpus extracted from the European Parliament web site by Philipp Koehn (University of Edinburgh). The main intended use is to aid statistical machine translation research. (Translated to Indonesian using Google Translate)
-#### [EuroPat](translation/europat)
-Parallel corpora of patents from the United States Patent and Trademark Office and from the European Patent Organisation. (Translated to Indonesian using Google Translate)
-#### [ParaCrawl](translation/paracrawl)
-Massively translated ParaCrawl v.7.1 from OPUS using Google Translate.

 ---
 license: mit
+task_categories:
+- text-classification
+language:
+- id
+pretty_name: indonesia-dataset-2023
 ---
+# Dataset Card for Indonesian NLP Dataset
+<!-- Provide a quick summary of the dataset. -->
+Koleksi kamus, korpus, dan dataset Natural Language Processing bahasa Indonesia.
+## Dataset Details
+### Dataset Description
+<!-- Provide a longer summary of what this dataset is. -->
+Dataset ini mencakup berbagai sumber data NLP dalam bahasa Indonesia, termasuk kamus, korpus teks, data multimodal, dan dataset untuk berbagai tugas NLP seperti klasifikasi teks, generasi teks, tanya jawab, terjemahan, summarization, dan pengenalan suara.
+- **Curated by:** Deddy Ratnanto
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Language(s) (NLP):** Indonesian (id)
+- **License:** CC-BY-SA 4.0
+### Dataset Sources [optional]
+<!-- Provide the basic links for the dataset. -->
+- **Repository:** [https://github.com/drat/indonesian_datasets](https://github.com/drat/indonesian_datasets)
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+## Uses
+<!-- Address questions around how the dataset is intended to be used. -->
+### Direct Use
+<!-- This section describes suitable use cases for the dataset. -->
+Dataset ini dapat digunakan untuk penelitian dan pengembangan model NLP dalam bahasa Indonesia, termasuk tetapi tidak terbatas pada klasifikasi teks, generasi teks, tanya jawab, terjemahan, summarization, dan pengenalan suara.
+### Out-of-Scope Use
+<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+Penggunaan untuk tujuan yang melanggar privasi, etika, atau hukum tidak dianjurkan. Dataset ini tidak dirancang untuk digunakan dalam aplikasi yang membutuhkan keakuratan tingkat tinggi tanpa validasi lebih lanjut.
+## Dataset Structure
+<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+Dataset ini terdiri dari berbagai subset yang masing-masing memiliki struktur dan format data yang berbeda. Berikut adalah beberapa subset yang termasuk dalam dataset ini:
+- **Crawl:**
+  - Kaskus WebText: Konten dari Kaskus dengan 3 cendol atau lebih.
+  - Twitter Puisi: Puisi dari berbagai pengguna di Twitter.
+  - Wikipedia Links: Konten dari tautan eksternal Wikipedia.
+- **Dictionary:**
+  - KBBI: Kamus Besar Bahasa Indonesia Daring.
+  - Wordlist: 105,226 kata dari Kamus Besar Bahasa Indonesia.
+- **Dump:**
+  - CC-News-ID: Berita dari CommonCrawl News dari 2016-2021.
+  - Javanese Text: Teks berbahasa Jawa.
+  - mC4: Data mC4 yang telah dibersihkan.
+  - Twitter: Dump dari ArchiveTeam Twitter Stream Grab.
+- **Multimodal:**
+  - CC3M: Conceptual Captions 3M dari Google Research.
+  - CC12M: Conceptual Captions 12M dari Google Research.
+  - YFCC100M OpenAI Subset: Subset YFCC100M OpenAI yang digunakan dalam dataset CLIP.
+- **Paraphrase:**
+  - MultiNLI: Multi-Genre Natural Language Inference.
+  - ParaBank: ParaBank v2.0.
+  - ParaNMT: ParaNMT, varian 5M.
+  - PAWS: PAWS dari Google Research.
+  - SBERT Paraphrase Data: Data paraphrase dari SBERT.
+  - SNLI: Stanford Natural Language Inference.
+- **Question Answering:**
+  - SQuAD: SQuAD dari Stanford University.
+  - Mathematics Dataset: Dataset soal matematika dari DeepMind.
+- **Speech:**
+  - Google TTS: Suara yang dihasilkan menggunakan Google Translate TTS.
+  - Unsupervised: Korpus besar suara bahasa Indonesia untuk pre-training model pengenalan suara.
+- **Summarization:**
+  - Gigaword: Gigaword dalam bahasa Inggris yang telah diterjemahkan.
+  - Reddit TLDR: 4 juta pasangan konten-ringkasan dari Webis-TLDR-17.
+  - WikiHow: Dataset summarization skala besar dari WikiHow.
+- **Translation:**
+  - Europarl: Korpus paralel dari European Parliament yang telah diterjemahkan menggunakan Google Translate.
+  - EuroPat: Korpora paralel dari patent US dan European Patent Organisation yang telah diterjemahkan.
+  - ParaCrawl: ParaCrawl v.7.1 yang diterjemahkan menggunakan Google Translate.
+## Dataset Creation
+### Curation Rationale
+<!-- Motivation for the creation of this dataset. -->
+Dataset ini dikurasi untuk menyediakan sumber daya NLP yang komprehensif dan berkualitas tinggi dalam bahasa Indonesia, mendukung penelitian dan pengembangan model NLP yang lebih baik.
+### Source Data
+<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+#### Data Collection and Processing
+<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
+Data dikumpulkan dari berbagai sumber termasuk website, media sosial, dan korpus yang tersedia secara publik. Proses pengumpulan data melibatkan scraping, filtering, dan normalisasi menggunakan berbagai alat dan perpustakaan NLP.
+#### Who are the source data producers?
+<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
+Produsen data mencakup berbagai individu dan organisasi yang mempublikasikan konten dalam bahasa Indonesia, termasuk penulis konten online, jurnalis, dan komunitas pengguna media sosial.
+### Annotations [optional]
+<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+#### Annotation process
+<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
+[More Information Needed]
+#### Who are the annotators?
+<!-- This section describes the people or systems who created the annotations. -->
+[More Information Needed]
+#### Personal and Sensitive Information
+<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
+Dataset ini mungkin mengandung data yang bersifat pribadi, sensitif, atau privasi. Proses anonimisasi dilakukan untuk menghilangkan informasi yang dapat mengidentifikasi individu secara langsung.
+## Bias, Risks, and Limitations
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+Dataset ini mungkin mengandung bias yang berasal dari sumber data asli. Ada risiko bahwa model yang dilatih dengan data ini akan mewarisi bias tersebut. Pengguna diharapkan melakukan evaluasi tambahan untuk mengidentifikasi dan mengatasi bias ini.
+### Recommendations
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+Pengguna disarankan untuk menyadari risiko, bias, dan keterbatasan teknis dari dataset ini. Evaluasi tambahan dan validasi diperlukan sebelum menggunakan model dalam aplikasi dunia nyata.
+## Citation [optional]
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+**BibTeX:**
+@inproceedings{deddy_ratnanto_2024,
+title={Indonesian NLP Dataset},
+author={Deddy Ratnanto},
+booktitle={Proceedings of the Indonesian NLP Conference},
+year={2024}
+}
+**APA:**
+Ratnanto, D. (2024). Indonesian NLP Dataset. Proceedings of the Indonesian NLP Conference.
+## Glossary [optional]
+<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
+[More Information Needed]
+## More Information [optional]
+[More Information Needed]
+## Dataset Card Authors [optional]
+Deddy Ratnanto
+## Dataset Card Contact
+[More Information Needed]