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README.md

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+---
+license: cc-by-4.0
+tags:
+- named-entity-recognition
+language:
+- ind
+---
+
+# indolem_ner_ugm
+
+NER UGM is a Named Entity Recognition dataset that comprises 2,343 sentences from news articles, and was constructed at the University of Gajah Mada based on five named entity classes: person, organization, location, time, and quantity.
+
+## Dataset Usage
+
+Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.
+
+## Citation
+
+```
+@inproceedings{koto-etal-2020-indolem,
+    title = "{I}ndo{LEM} and {I}ndo{BERT}: A Benchmark Dataset and Pre-trained Language Model for {I}ndonesian {NLP}",
+    author = "Koto, Fajri  and
+      Rahimi, Afshin  and
+      Lau, Jey Han  and
+      Baldwin, Timothy",
+    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
+    month = dec,
+    year = "2020",
+    address = "Barcelona, Spain (Online)",
+    publisher = "International Committee on Computational Linguistics",
+    url = "https://aclanthology.org/2020.coling-main.66",
+    doi = "10.18653/v1/2020.coling-main.66",
+    pages = "757--770"
+}
+@phdthesis{fachri2014pengenalan,
+  title     = {Pengenalan Entitas Bernama Pada Teks Bahasa Indonesia Menggunakan Hidden Markov Model},
+  author    = {FACHRI, MUHAMMAD},
+  year      = {2014},
+  school    = {Universitas Gadjah Mada}
+}
+```
+
+## License
+
+Creative Commons Attribution 4.0
+
+## Homepage
+
+[https://indolem.github.io/](https://indolem.github.io/)
+
+### NusaCatalogue
+
+For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)