Update README.md

README.md

@@ -1,3 +1,56 @@
 ---
-license: mit
+annotations_creators:
+- unknown
+language_creators:
+- unknown
+languages:
+- en
+licenses:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- unknown
+task_categories:
+- deduplication
+task_ids:
+- deduplication
+- natural-language-inference
+- semantic-similarity-scoring
+- text-scoring
+pretty_name: CORE Deduplication of Scholarly Documents
 ---
+
+# Dataset Card for CORE Deduplication
+
+## Dataset Description
+
+- **Homepage:** [https://core.ac.uk/about/research-outputs](https://core.ac.uk/about/research-outputs)
+- **Repository:** [https://core.ac.uk/datasets/core_2020-05-10_deduplication.zip](https://core.ac.uk/datasets/core_2020-05-10_deduplication.zip)
+- **Paper:** [Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings](http://oro.open.ac.uk/id/eprint/70519)
+- **Point of Contact:** [CORE Team](https://core.ac.uk/about#contact)
+- **Size of downloaded dataset files:** 204 MB
+
+### Dataset Summary
+
+CORE 2020 Deduplication dataset (https://core.ac.uk/documentation/dataset) contains 100K scholarly documents labeled as duplicates/non-duplicates.
+
+### Languages
+
+The dataset language is English (BCP-47 `en`)
+
+### Citation Information
+
+```
+@inproceedings{dedup2020,
+  title={Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings},
+  author={Gyawali, Bikash and Anastasiou, Lucas and Knoth, Petr},
+  booktitle = {Proceedings of 12th Language Resources and Evaluation Conference},
+  month = may,
+  year = 2020,
+  publisher = {France European Language Resources Association},
+  pages = {894-903}
+}
+```