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README.md

@@ -5,14 +5,21 @@ language:
 - ind
 ---
 
+# keps
+
 The KEPS dataset (Mahfuzh, Soleman and Purwarianti, 2019) consists of text from Twitter
+
 discussing banking products and services and is written in the Indonesian language. A phrase
+
 containing important information is considered a keyphrase. Text may contain one or more
+
 keyphrases since important phrases can be located at different positions.
+
 - tokens: a list of string features.
+
 - seq_label: a list of classification labels, with possible values including O, B, I.
-The labels use Inside-Outside-Beginning (IOB) tagging.
 
+The labels use Inside-Outside-Beginning (IOB) tagging.
 
 ## Dataset Usage
 
@@ -20,7 +27,8 @@ Run `pip install nusacrowd` before loading the dataset through HuggingFace's `lo
 
 ## Citation
 
-```@inproceedings{mahfuzh2019improving,
+```
+@inproceedings{mahfuzh2019improving,
   title={Improving Joint Layer RNN based Keyphrase Extraction by Using Syntactical Features},
   author={Miftahul Mahfuzh, Sidik Soleman, and Ayu Purwarianti},
   booktitle={Proceedings of the 2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA)},
@@ -36,6 +44,8 @@ Creative Common Attribution Share-Alike 4.0 International
 
 ## Homepage
 
+[https://github.com/IndoNLP/indonlu](https://github.com/IndoNLP/indonlu)
+
 ### NusaCatalogue
 
 For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)