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A Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia

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NLP Bahasa Indonesia Resources

This repository provides link to useful dataset and another resources for NLP in Bahasa Indonesia.

Last Update: 23 Aug 2021

Table of contents

Corpus

Named Entity Recognition

1) Product NER. https://github.com/dziem/proner-labeled-text 2) NER-grit. https://github.com/grit-id/nergrit-corpus

POS-Tagging

1) IDN Tagged Corpus. https://github.com/famrashel/idn-tagged-corpus 2) Indonesian Part-of-Speech (POS) Tagging. https://github.com/kmkurn/id-pos-tagging/blob/master/data/dataset.tar.gz

Question and Answering

1) TydiQA. https://github.com/google-research-datasets/tydiqa

Paraphrasing

1) Quora Paraphrasing. https://github.com/louisowen6/quoraparaphrasingid 2) Paraphrase Adversaries from Word Scrambling. https://github.com/Wikidepia/indonesian_datasets/tree/master/paraphrase/paws

Text Summarization

1) Indosum. https://github.com/kata-ai/indosum 2) Liputan6. https://huggingface.co/datasets/id_liputan6

Hate-speech

1) ID Multi Label Hate Speech. https://github.com/okkyibrohim/id-multi-label-hate-speech-and-abusive-language-detection

Word Analogy

1) KAWAT. https://github.com/kata-ai/kawat

Formal-Informal

1) STIF-Indonesia. https://github.com/haryoa/stif-indonesia 2) IndoCollex. https://github.com/haryoa/indo-collex

Multilingual Parallel

1) https://huggingface.co/datasets/alt 2) https://opus.nlpl.eu/bible-uedin.php 3) http://www.statmt.org/cc-aligned/ 4) https://huggingface.co/datasets/idpanlbppt 5) https://huggingface.co/datasets/opensubtitles 6) https://huggingface.co/datasets/opus100 7) https://huggingface.co/datasets/tapaco 8) https://huggingface.co/datasets/wikilingua

Unsupervised Corpus

1) OSCAR. https://oscar-corpus.com/ 2) Online Newspaper. https://github.com/feryandi/Dataset-Artikel 3) IndoNLU. https://huggingface.co/datasets/indonlu 4) http://data.statmt.org/cc-100/ 5) https://huggingface.co/datasets/idclickbait 6) https://huggingface.co/datasets/idnewspapers_2018 7) https://opus.nlpl.eu/QED.php

Voice-Text

1) https://huggingface.co/datasets/common_voice 2) https://huggingface.co/datasets/covost2

Puisi and Pantun

1) https://github.com/ilhamfp/puisi-pantun-generator

Dictionary

Synonym

1) https://github.com/victoriasovereigne/tesaurus

Sentiment

1) (Negative) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/negatifta2.txt 2) (Negative) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/negativeadd.txt 3) (Negative) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/negativekeyword.txt 4) (Negative) https://github.com/masdevid/ID-OpinionWords/blob/master/negative.txt 5) (Positive) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/positifta2.txt 6) (Positive) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/positiveadd.txt 7) (Positive) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/positivekeyword.txt 8) (Positive) https://github.com/masdevid/ID-OpinionWords/blob/master/positive.txt 9) (Score) https://github.com/agusmakmun/SentiStrengthID/blob/master/iddict/sentimentword.txt 10) (InSet Lexicon) https://github.com/fajri91/InSet [Paper] 11) (Twitter Labelled Sentiment) https://www.researchgate.net/profile/RidiFerdiana/publication/339936724IndonesianSentimentTwitterDataset/data/5e6d64c6a6fdccf994ca18aa/Indonesian-Sentiment-Twitter-Dataset.zip?origin=publicationDetaillinkedData [Paper] 12) https://huggingface.co/datasets/sentilex

Position or Degree

1) https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/psuf.txt 2) https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/lldr.txt 3) https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/opos.txt 4) https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/ptit.txt

Root Words

1) https://github.com/agusmakmun/SentiStrengthID/blob/master/id_dict/rootword.txt 2) https://github.com/sastrawi/sastrawi/blob/master/data/kata-dasar.original.txt 3) https://github.com/sastrawi/sastrawi/blob/master/data/kata-dasar.txt 4) https://github.com/prasastoadi/serangkai/blob/master/serangkai/kamus/data/kamus-kata-dasar.csv

I have made the combined root words list from all of the above repositories.

Slang Words

1) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/kbba.txt 2) https://github.com/agusmakmun/SentiStrengthID/blob/master/id_dict/slangword.txt 3) https://github.com/panggi/pujangga/blob/master/resource/formalization/formalizationDict.txt

I have made the combined slang words dictionary from all of the above repositories.

Stop Words

1) https://github.com/yasirutomo/python-sentianalysis-id/blob/master/data/feature_list/stopwordsID.txt 2) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/stopword.txt 3) https://github.com/abhimantramb/elang/tree/master/word2vec/utils/stopwords-list

I have made the combined stop words list from all of the above repositories.

Swear Words

1) https://github.com/abhimantramb/elang/blob/master/word2vec/utils/swear-words.txt

Composite Words

1) https://github.com/panggi/pujangga/blob/master/resource/tokenizer/compositewords.txt

Number Words

1) https://github.com/panggi/pujangga/blob/master/resource/netagger/morphologicalfeature/number.txt

Calendar Words

1) https://github.com/onlyphantom/elang/blob/master/build/lib/elang/word2vec/utils/negative/calendar-words.txt

Emoticon

1) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/emoticon.txt 2) https://github.com/jolicode/emoji-search/blob/master/synonyms/cldr-emoji-annotation-synonyms-id.txt 3) https://github.com/agusmakmun/SentiStrengthID/blob/master/id_dict/emoticon.txt

Acronym

1) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/acronym.txt 2) https://github.com/panggi/pujangga/blob/master/resource/sentencedetector/acronym.txt 3) https://id.wiktionary.org/wiki/Lampiran:DaftarsingkatandanakronimdalambahasaIndonesia#A

Indonesia Region

1) https://github.com/abhimantramb/elang/blob/master/word2vec/utils/indonesian-region.txt 2) https://github.com/edwardsamuel/Wilayah-Administratif-Indonesia/tree/master/csv 3) https://github.com/pentagonal/Indonesia-Postal-Code/tree/master/Csv

Country

1) https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/country.txt

Region

1) https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/lpre.txt

Title of Name

1) https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/ppre.txt

Gender by Name

1) https://github.com/seuriously/genderprediction/blob/master/namatraining.txt

Organization

1) https://github.com/panggi/pujangga/blob/master/resource/reference/opre.txt

Articles and Papers

POS-Tagging

1) https://medium.com/@puspitakaban/pos-tagging-bahasa-indonesia-dengan-flair-nlp-c12e45542860 2) Manually Tagged Indonesian Corpus [Paper] [GitHub]

Word Embedding

1) (FastText). https://structilmy.com/2019/08/membuat-model-word-embedding-fasttext-bahasa-indonesia/ 2) (Word2Vec). https://yudiwbs.wordpress.com/2018/03/31/word2vec-wikipedia-bahasa-indonesia-dengan-python-gensim/

Topic Analysis

1) (Introduction to LSA & LDA). https://monkeylearn.com/blog/introduction-to-topic-modeling/ 2) (Introduction to LDA w/ Code & Tips). https://www.analyticsvidhya.com/blog/2016/08/beginners-guide-to-topic-modeling-in-python/ 3) (Topic Modeling Methods Comparison Paper). https://thesai.org/Downloads/Volume6No1/Paper21-ASurveyofTopicModelinginTextMining.pdf 4) (Original LDA Paper). http://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf 5) (LDA Python Library). https://pypi.org/project/lda/; https://radimrehurek.com/gensim/models/ldamodel.html; https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.LatentDirichletAllocation.html 6) (Original CTM Paper). http://people.ee.duke.edu/~lcarin/Blei2005CTM.pdf 7) (CTM Python Library). https://pypi.org/project/tomotopy/; https://github.com/kzhai/PyCTM 8) (Gaussian LDA Paper). https://www.aclweb.org/anthology/P15-1077.pdf 9) (Gaussian LDA Library). https://github.com/rajarshd/GaussianLDA 10) (Temporal Topic Modeling Comparison Paper). https://thesai.org/Downloads/Volume6No1/Paper21-ASurveyofTopicModelinginTextMining.pdf 11) (TOT: A Non-Markov Continuous-Time Model of Topical Trends Paper). https://people.cs.umass.edu/~mccallum/papers/tot-kdd06s.pdf 12) (TOT Library). https://github.com/ahmaurya/topicsover_time
13) (Example of LDA in Bahasa Project Code). https://github.com/kirralabs/text-clustering

Text Classification

Zero-shot Learning

1) (Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach) https://arxiv.org/pdf/1909.00161.pdf | https://github.com/yinwenpeng/BenchmarkingZeroShot 2) (Integrating Semantic Knowledge to Tackle Zero-shot Text Classification) https://arxiv.org/abs/1903.12626 | https://github.com/JingqingZ/KG4ZeroShotText 3) (Train Once, Test Anywhere: Zero-Shot Learning for Text Classification) https://arxiv.org/abs/1712.05972 | https://amitness.com/2020/05/zero-shot-text-classification/ 4) (Zero-shot Text Classification With Generative Language Models) https://arxiv.org/abs/1912.10165 | https://amitness.com/2020/06/zero-shot-classification-via-generation/ 5) (Zero-shot User Intent Detection via Capsule Neural Networks) https://arxiv.org/abs/1809.00385 | https://github.com/congyingxia/ZeroShotCapsule

Few-shot Learning

1) (Few-shot Text Classification with Distributional Signatures) https://arxiv.org/pdf/1908.06039.pdf | https://github.com/YujiaBao/Distributional-Signatures 2) (Few Shot Text Classification with a Human in the Loop) https://katbailey.github.io/talks/Few-shot%20text%20classification.pdf | https://github.com/katbailey/few-shot-text-classification 3) (Induction Networks for Few-Shot Text Classification) https://arxiv.org/pdf/1902.10482v2.pdf | https://github.com/zhongyuchen/few-shot-learning

Pre-trained Models

1) Indo-BERT. https://github.com/indobenchmark/indonlu & https://huggingface.co/indobenchmark/indobert-base-p1 1) Transformer-based Pre-trained Model in Bahasa. https://github.com/cahya-wirawan/indonesian-language-models/tree/master/Transformers 1) Generate Word-Embedding / Sentence-Embedding using pre-Trained Multilingual Bert model. (https://colab.research.google.com/drive/1yFphU6PW9Uo6lmDly_ud9a6c4RCYlwdX#scrollTo=Zn0n2S-FWZih). P.S: Just change the model using 'bert-base-multilingual-uncased' 2) https://github.com/meisaputri21/Indonesian-Twitter-Emotion-Dataset. [Paper] 3) https://github.com/Kyubyong/wordvectors 4) https://drive.google.com/uc?id=0B5YTktu2dOKKNUY1OWJORlZTcUU&export=download 5) https://github.com/deryrahman/word2vec-bahasa-indonesia 6) https://sites.google.com/site/rmyeid/projects/polyglot

Usable Library

1) Pujangga: Indonesian Natural Language Processing REST API. https://github.com/panggi/pujangga 2) Sastrawi Stemmer Bahasa Indonesia. https://github.com/sastrawi/sastrawi 3) NLP-ID. https://github.com/kumparan/nlp-id 4) MorphInd: Indonesian Morphological Analyzer. http://septinalarasati.com/morphind/ 5) INDRA: Indonesian Resource Grammar. https://github.com/davidmoeljadi/INDRA 6) Typo Checker. https://github.com/mamat-rahmat/checker_id 7) Multilingual NLP Package. https://github.com/flairNLP/flair 9) spaCy [GitHub] [Tutorial] 9) https://github.com/yohanesgultom/nlp-experiments 10) https://github.com/yasirutomo/python-sentianalysis-id 11) https://github.com/riochr17/Analisis-Sentimen-ID 12) https://github.com/yusufsyaifudin/indonesia-ner

Spelling Correction

You can adjust this code with Bahasa corpus to do the spelling correction

Twitter Scraping

1) GetOldTweets3. https://github.com/Mottl/GetOldTweets3

Usage:

bash
import GetOldTweets3 as got
tweetCriteria=got.manager.TweetCriteria().setQuerySearch('#CoronaVirusIndonesia').setSince("2020-01-01").setUntil("2020-03-05").setNear("Jakarta, Indonesia").setLang("id")
tweets=got.manager.TweetManager.getTweets(tweetCriteria)
for tweet in tweets:
    print(tweet.username)
    print(tweet.text)
    print(tweet.date)
    print("tweet.to")
    print("tweet.retweets")
    print("tweet.favorites")
    print("tweet.mentions")
    print("tweet.hashtags")
    print("tweet.geo")

2) Tweepy. http://docs.tweepy.org/en/latest/

Step-by-step how to use Tweepy. https://towardsdatascience.com/how-to-scrape-tweets-from-twitter-59287e20f0f1

Sign in to Twitter Developer. https://developer.twitter.com/en

Full List of Tweets Object. https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/tweet-object

Increasing Tweepy’s standard API search limit. https://bhaskarvk.github.io/2015/01/how-to-use-twitters-search-rest-api-most-effectively./

Other Resources

1) https://github.com/irfnrdh/Awesome-Indonesia-NLP 2) https://github.com/kirralabs/indonesian-NLP-resources 3) https://huggingface.co/datasets?filter=languages%3Aid&p=0

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