---
language:
- en
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
pretty_name: MS MARCO corpus
dataset_info:
- config_name: passage
  features:
  - name: pid
    dtype: int64
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 3089201649
    num_examples: 8841823
  download_size: 1688656108
  dataset_size: 3089201649
- config_name: query
  features:
  - name: qid
    dtype: int64
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 48033044
    num_examples: 1010916
  download_size: 34858846
  dataset_size: 48033044
configs:
- config_name: passage
  data_files:
  - split: train
    path: passage/train-*
- config_name: query
  data_files:
  - split: train
    path: queries/train-*
---

# MS MARCO Corpus

This dataset allows for a convenient mapping from MS MARCO query/passage ID to the query/passage text. This passage corpus was downloaded from https://msmarco.z22.web.core.windows.net/msmarcoranking/collection.tar.gz, and the queries from https://msmarco.blob.core.windows.net/msmarcoranking/queries.tar.gz (via Wayback Machine).

## Usage

This dataset was designed to allow you to perform the following:
```python
from datasets import load_dataset

query_dataset = load_dataset("sentence-transformers/msmarco-corpus", "query", split="train")
qid_to_query = dict(zip(query_dataset["qid"], query_dataset["text"]))
print(qid_to_query[571018])
# => "what are the liberal arts?"

passage_dataset = load_dataset("sentence-transformers/msmarco-corpus", "passage", split="train")
pid_to_passage = dict(zip(passage_dataset["pid"], passage_dataset["text"]))
print(pid_to_passage[7349777])
# => "liberal arts. 1. the academic course of instruction at a college intended to provide general knowledge and comprising the arts, humanities, natural sciences, and social sciences, as opposed to professional or technical subjects."
```

## Related Datasets

This dataset is used for the query and passage texts in the following datasets containing MS MARCO with mined hard negatives.

* [msmarco-bm25](https://huggingface.co/datasets/sentence-transformers/msmarco-bm25)
* [msmarco-msmarco-distilbert-base-tas-b](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-tas-b)
* [msmarco-msmarco-distilbert-base-v3](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3)
* [msmarco-msmarco-MiniLM-L-6-v3](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-MiniLM-L-6-v3)
* [msmarco-distilbert-margin-mse-cls-dot-v2](https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-cls-dot-v2)
* [msmarco-distilbert-margin-mse-cls-dot-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-cls-dot-v1)
* [msmarco-distilbert-margin-mse-mean-dot-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-mean-dot-v1)
* [msmarco-mpnet-margin-mse-mean-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-mpnet-margin-mse-mean-v1)
* [msmarco-co-condenser-margin-mse-cls-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-co-condenser-margin-mse-cls-v1)
* [msmarco-distilbert-margin-mse-mnrl-mean-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-mnrl-mean-v1)
* [msmarco-distilbert-margin-mse-sym-mnrl-mean-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-sym-mnrl-mean-v1)
* [msmarco-distilbert-margin-mse-sym-mnrl-mean-v2](https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-sym-mnrl-mean-v2)
* [msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1)