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README.md

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----
-annotations_creators:
-- unknown
-language_creators:
-- unknown
-language:
-- en
-license:
-- mit
-multilinguality:
-- monolingual
-size_categories:
-- 100K<n<1M
-source_datasets:
-- unknown
-task_categories:
-- other
-task_ids:
-- natural-language-inference
-- semantic-similarity-scoring
-- text-scoring
-pretty_name: CORE Deduplication of Scholarly Documents
-tags:
-- deduplication
----
-
-# 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}
-}
-```

train.jsonl → pinecone--core-2020-05-10-deduplication/json-train.parquet

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