Create README.md

Dataset Summary
Starting with a paper released at NIPS 2016, MS MARCO is a collection of datasets focused on deep learning in search.

The first dataset was a question answering dataset featuring 100,000 real Bing questions and a human generated answer. Since then we released a 1,000,000 question dataset, a natural langauge generation dataset, a passage ranking dataset, keyphrase extraction dataset, crawling dataset, and a conversational search.

There have been 277 submissions. 20 KeyPhrase Extraction submissions, 87 passage ranking submissions, 0 document ranking submissions, 73 QnA V2 submissions, 82 NLGEN submisions, and 15 QnA V1 submissions

This data comes in three tasks/forms: Original QnA dataset(v1.1), Question Answering(v2.1), Natural Language Generation(v2.1).

The original question answering datset featured 100,000 examples and was released in 2016. Leaderboard is now closed but data is availible below.

The current competitive tasks are Question Answering and Natural Language Generation. Question Answering features over 1,000,000 queries and is much like the original QnA dataset but bigger and with higher quality. The Natural Language Generation dataset features 180,000 examples and builds upon the QnA dataset to deliver answers that could be spoken by a smart speaker.

version v1.1

Supported Tasks
More Information Needed

Languages
More Information Needed

Dataset Structure
We show detailed information for up to 5 configurations of the dataset.

Data Instances
v1.1
Size of downloaded dataset files: 160.88 MB
Size of the generated dataset: 414.48 MB
Total amount of disk used: 575.36 MB
An example of 'train' looks as follows.

v2.1
Size of downloaded dataset files: 1320.14 MB
Size of the generated dataset: 4088.84 MB
Total amount of disk used: 5408.98 MB
An example of 'validation' looks as follows.

Data Fields
The data fields are the same among all splits.

v1.1
answers: a list of string features.
passages: a dictionary feature containing:
is_selected: a int32 feature.
passage_text: a string feature.
url: a string feature.
query: a string feature.
query_id: a int32 feature.
query_type: a string feature.
wellFormedAnswers: a list of string features.
v2.1
answers: a list of string features.
passages: a dictionary feature containing:
is_selected: a int32 feature.
passage_text: a string feature.
url: a string feature.
query: a string feature.
query_id: a int32 feature.
query_type: a string feature.
wellFormedAnswers: a list of string features.
Data Splits Sample Size
name train validation test
v1.1 82326 10047 9650
v2.1 808731 101093 101092
Dataset Creation
Curation Rationale
More Information Needed

Source Data
More Information Needed

Annotations
More Information Needed

Personal and Sensitive Information
More Information Needed

Considerations for Using the Data
Social Impact of Dataset
More Information Needed

Discussion of Biases
More Information Needed

README.md

@@ -0,0 +1,44 @@
+# Dataset Summary
+Starting with a paper released at NIPS 2016, MS MARCO is a collection of datasets focused on deep learning in search.
+
+
+# Dataset Creation
+
+## Source Data
+More Information Needed
+
+## Annotations
+More Information Needed
+
+## Personal and Sensitive Information
+More Information Needed
+
+# Considerations for Using the Data
+## Social Impact of Dataset
+More Information Needed
+
+## Discussion of Biases
+More Information Needed
+
+## Other Known Limitations
+More Information Needed
+
+# Additional Information
+## Dataset Curators
+@spacemanidol
+
+# Licensing Information
+The MS MARCO datasets are intended for non-commercial research purposes only to promote advancement in the field of artificial intelligence and related areas, and is made available free of charge without extending any license or other intellectual property rights. The dataset is provided “as is” without warranty and usage of the data has risks since we may not own the underlying rights in the documents. We are not be liable for any damages related to use of the dataset. Feedback is voluntarily given and can be used as we see fit. Upon violation of any of these terms, your rights to use the dataset will end automatically.
+
+Please contact us at ms-marco@microsoft.com if you own any of the documents made available but do not want them in this dataset. We will remove the data accordingly. If you have questions about use of the dataset or any research outputs in your products or services, we encourage you to undertake your own independent legal review. For other questions, please feel free to contact us.
+
+# Citation Information
+@article{Campos2016MSMA,
+  title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
+  author={Daniel Fernando Campos and T. Nguyen and M. Rosenberg and Xia Song and Jianfeng Gao and Saurabh Tiwary and Rangan Majumder and L. Deng and Bhaskar Mitra},
+  journal={ArXiv},
+  year={2016},
+  volume={abs/1611.09268}
+}
+#Contributions
+@spacemanidol