Create README.md

README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+language:
+- en
+license:
+- other
+multilinguality:
+- monolingual
+pretty_name: WCEP-10
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- summarization
+task_ids:
+- news-articles-summarization
+paperswithcode_id: wcep
+train-eval-index:
+- config: default
+  task: summarization
+  task_id: summarization
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    document: text
+    summary: target
+  metrics:
+    - type: rouge
+      name: Rouge
+---
+
+This is a copy of the [WCEP-10](https://huggingface.co/datasets/ccdv/WCEP-10) dataset, except the input source documents of its `test` split have been replaced by a __dense__ retriever. The retrieval pipeline used:
+
+- __query__: The `summary` field of each example
+- __corpus__: The union of all documents in the `train`, `validation` and `test` splits
+- __retriever__: [`facebook/contriever-msmarco`](https://huggingface.co/facebook/contriever-msmarco) via [PyTerrier](https://pyterrier.readthedocs.io/en/latest/) with default settings
+- __top-k strategy__: `"oracle"`, i.e. the number of documents retrieved, `k`, is set as the original number of input documents for each example
+
+Retrieval results on the `test` set:
+
+|ndcg | recall@100 | recall@1000 | Rprec |
+| ----------- | ----------- | ----------- | ----------- |
+| 0.8231      | 0.8678      | 0.9263      | 0.6631      |