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Datasets:
SEACrowd
/
identic

Languages:
Indonesian
English
Tags:
machine-translation
pos-tagging
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identic

IDENTIC is an Indonesian-English parallel corpus for research purposes.

The corpus is a bilingual corpus paired with English. The aim of this work is to build and provide

researchers a proper Indonesian-English textual data set and also to promote research in this language pair.

The corpus contains texts coming from different sources with different genres.

Additionally, the corpus contains tagged texts that follows MorphInd tagset (Larasati et. al., 2011).

Dataset Usage

Run pip install nusacrowd before loading the dataset through HuggingFace's load_dataset.

Citation 

@inproceedings{larasati-2012-identic,
    title = "{IDENTIC} Corpus: Morphologically Enriched {I}ndonesian-{E}nglish Parallel Corpus",
    author = "Larasati, Septina Dian",
    booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
    month = may,
    year = "2012",
    address = "Istanbul, Turkey",
    publisher = "European Language Resources Association (ELRA)",
    url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/644_Paper.pdf",
    pages = "902--906",
    abstract = "This paper describes the creation process of an Indonesian-English parallel corpus (IDENTIC).
    The corpus contains 45,000 sentences collected from different sources in different genres.
    Several manual text preprocessing tasks, such as alignment and spelling correction, are applied to the corpus
    to assure its quality. We also apply language specific text processing such as tokenization on both sides and
    clitic normalization on the Indonesian side. The corpus is available in two different formats: ‘plain',
    stored in text format and ‘morphologically enriched', stored in CoNLL format. Some parts of the corpus are
    publicly available at the IDENTIC homepage.",
}

License

CC BY-NC-SA 3.0

Homepage

https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0005-BF85-F

NusaCatalogue

For easy indexing and metadata: https://indonlp.github.io/nusa-catalogue

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