allenai/wcep_sparse_oracle

---
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dataset, except the input source documents of its `test` split have been replaced by a __sparse__ retriever.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__: BM25 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 `train` set:

| Recall@100 | Rprec | Precision@k | Recall@k |
| ----------- | ----------- | ----------- | ----------- |
| 0.8753 | 0.6443 | 0.6443 | 0.6443 |

Retrieval results on the `validation` set:

| Recall@100 | Rprec | Precision@k | Recall@k |
| ----------- | ----------- | ----------- | ----------- |
| 0.8706 | 0.6280 | 0.6280 | 0.6280 |

Retrieval results on the `test` set:

| Recall@100 | Rprec | Precision@k | Recall@k |
| ----------- | ----------- | ----------- | ----------- |
| 0.8836 | 0.6658 | 0.6658 | 0.6658 |

原始信息汇总

数据集概述

基本信息

• 名称: WCEP-10
• 语言: 英语 (en)
• 许可证: 其他 (other)
• 多语言性: 单语 (monolingual)
• 大小: 1K<n<10K
• 来源: 原始 (original)

创建者信息

• 标注创建者: 专家生成 (expert-generated)
• 语言创建者: 专家生成 (expert-generated)

任务与结构

• 任务类别: 摘要 (summarization)
• 任务ID: news-articles-summarization
• 训练与评估索引:
  • 配置: 默认 (default)
  • 任务: 摘要 (summarization)
  • 任务ID: 摘要 (summarization)
  • 分割:
    • 训练分割: train
    • 评估分割: test
  • 列映射:
    • 文档: text
    • 摘要: target
  • 评估指标:
    • 类型: rouge
    • 名称: Rouge

特殊处理

• 测试集输入源文档: 被稀疏检索器替换
• 检索流程:
  • 查询: 每个示例的summary字段
  • 文档库: train, validation 和 test 分割中的所有文档的联合
  • 检索器: BM25，通过PyTerrier使用默认设置
  • 顶部-k策略: "oracle"，即检索的文档数量k设置为每个示例原始输入文档的数量

检索结果

• 训练集:
  • Recall@100: 0.8753
  • Rprec: 0.6443
  • Precision@k: 0.6443
  • Recall@k: 0.6443
• 验证集:
  • Recall@100: 0.8706
  • Rprec: 0.6280
  • Precision@k: 0.6280
  • Recall@k: 0.6280
• 测试集:
  • Recall@100: 0.8836
  • Rprec: 0.6658
  • Precision@k: 0.6658
  • Recall@k: 0.6658