---
dataset_info:
  features:
  - name: query
    dtype: string
  - name: hits
    list:
    - name: content
      dtype: string
    - name: docid
      dtype: string
    - name: qid
      dtype: int64
    - name: rank
      dtype: int64
    - name: score
      dtype: float64
  splits:
  - name: train
    num_bytes: 154379410
    num_examples: 21100
  download_size: 5482226
  dataset_size: 154379410
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

This is reranking dataset built from 179 queris from [MSMARCO-V2 passages set](https://ir-datasets.com/msmarco-passage-v2.html).

Below are the data creation process:

```
# Multiple Random Sampling

import copy
import random
replicate_rank_results = []
replicate_times = 100
for item in combined_rank_results:
    for _ in range(replicate_times):
        new_item = copy.deepcopy(item)
        # Randomly select 20 hits from original hits list
        random_select_index = random.sample(range(len(item['hits'])), min(20, len(item['hits'])))
        random_select_index.sort()
        new_item['hits'] = [new_item['hits'][i] for i in random_select_index]
        replicate_rank_results.append(new_item)
print(len(replicate_rank_results))

```