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README.md

@@ -6,8 +6,9 @@ language:
 - eng
 ---
 
-TED En-Id is a machine translation dataset containing Indonesian-English parallel sentences collected from the TED talk transcripts. We split the dataset and use 75% as the training set, 10% as the validation set, and 15% as the test set. Each of the datasets is evaluated in both directions, i.e., English to Indonesian (En → Id) and Indonesian to English (Id → En) translations.
+# ted_en_id
 
+TED En-Id is a machine translation dataset containing Indonesian-English parallel sentences collected from the TED talk transcripts. We split the dataset and use 75% as the training set, 10% as the validation set, and 15% as the test set. Each of the datasets is evaluated in both directions, i.e., English to Indonesian (En → Id) and Indonesian to English (Id → En) translations.
 
 ## Dataset Usage
 
@@ -15,7 +16,8 @@ Run `pip install nusacrowd` before loading the dataset through HuggingFace's `lo
 
 ## Citation
 
-```@inproceedings{qi2018and,
+```
+@inproceedings{qi2018and,
   title={When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?},
   author={Qi, Ye and Sachan, Devendra and Felix, Matthieu and Padmanabhan, Sarguna and Neubig, Graham},
   booktitle={Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)},
@@ -55,6 +57,8 @@ Creative Commons Attribution Share-Alike 4.0 International
 
 ## Homepage
 
+[https://github.com/IndoNLP/indonlg](https://github.com/IndoNLP/indonlg)
+
 ### NusaCatalogue
 
 For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)