ms2_sparse_oracle

This is a copy of the [MS^2](https://huggingface.co/datasets/allenai/mslr2022) dataset, except the input source documents of its `validation` split have been replaced by a __sparse__ retriever. The retrieval pipeline used:

- __query__: The `background` field of each example
- __corpus__: The union of all documents in the `train`, `validation` and `test` splits. A document is the concatenation of the `title` and `abstract`.
- __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 |
| ----------- | ----------- | ----------- | ----------- |
| 0.4333 | 0.2163 | 0.2163 | 0.2163 |

Retrieval results on the `validation` set:

| Recall@100 | Rprec | Precision@k | Recall@k |
| ----------- | ----------- | ----------- | ----------- |
| 0.3780 | 0.1827 | 0.1827 | 0.1827 |

Retrieval results on the `test` set:

| Recall@100 | Rprec | Precision@k | Recall@k |
| ----------- | ----------- | ----------- | ----------- |
| 0.3928 | 0.1898 | 0.1898 | 0.1898 |

本数据集为[MS^2](https://huggingface.co/datasets/allenai/mslr2022)的复刻版本，仅将其`validation`（验证）划分的输入源文档替换为**稀疏检索器（sparse retriever）**所获取的文档。所用检索流水线如下：
- 查询（query）：每个样本的`background`（背景）字段
- 语料库（corpus）：`train`（训练）、`validation`（验证）与`test`（测试）划分下的全部文档的并集；单篇文档由`title`（标题）与`abstract`（摘要）拼接得到
- 检索器（retriever）：基于[PyTerrier](https://pyterrier.readthedocs.io/en/latest/)实现的BM25检索模型，采用默认参数配置
- Top-k策略：采用“神谕（oracle）”策略，即检索返回的文档数`k`设置为每个样本原始的输入文档数目

### 训练集检索结果
| 召回率@100 | R-precision | 精确率@k | 召回率@k |
| :---------- | :---------- | :------- | :------- |
| 0.4333 | 0.2163 | 0.2163 | 0.2163 |

### 验证集检索结果
| 召回率@100 | R-precision | 精确率@k | 召回率@k |
| :---------- | :---------- | :------- | :------- |
| 0.3780 | 0.1827 | 0.1827 | 0.1827 |

### 测试集检索结果
| 召回率@100 | R-precision | 精确率@k | 召回率@k |
| :---------- | :---------- | :------- | :------- |
| 0.3928 | 0.1898 | 0.1898 | 0.1898 |