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Dataset Card for Multi-Document
Dataset Summary
Multi-Document, a large-scale multi-document summarization dataset created from scientific articles. Multi-Document introduces a challenging multi-document summarization task: writing the related-work section of a paper based on its abstract and the articles it references.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The text in the dataset is in English
Dataset Structure
Data Instances
{"id": "n3ByHGrxH3bvfrvF", "docs": [{"id": "1394519630182457344", "text": "Clover Bio's COVID-19 vaccine candidate shows immune response against SARS-CoV-2 variants in mouse model https://t.co/wNWa9GQux5"}, {"id": "1398154482463170561", "text": "The purpose of the Vaccine is not to stop you from catching COVID 19. The vaccine introduces the immune system to an inactivated form of the SARS-CoV-2 coronavirus or a small part of it. This then equips the body with the ability to fight the virus better in case you get it. https://t.co/Cz9OU6Zi7P"}, {"id": "1354844652520792071", "text": "The Moderna mRNA COVID-19 vaccine appears to be effective against the novel, rapidly spreading variants of SARS-CoV-2.\nResearchers analysed blood samples from vaccinated people and monkeys- Both contained neutralising antibodies against the virus. \nPT1/2\n#COVID19vaccines #biotech https://t.co/ET1maJznot"}, {"id": "1340189698107518976", "text": "@KhandaniM Pfizer vaccine introduces viral surface protein which is constant accross SARS COV 2 variants into the body. Body builds antibodies against this protein, not any virus. These antibodies instructs macrophages & T-Cells to attack & destroy any COVID-19 v variant at infection point"}, {"id": "1374368989581778945", "text": "@DelthiaRicks " Pfizer and BioNTech\u2019s COVID-19 vaccine is an mRNA vaccine, which does not use the live virus but rather a small portion of the viral sequence of the SARS-CoV-2 virus to instruct the body to produce the spike protein displayed on the surface of the virus.""}, {"id": "1353354819315126273", "text": "Pfizer and BioNTech Publish Results of Study Showing COVID-19 Vaccine Elicits Antibodies that Neutralize Pseudovirus Bearing the SARS-CoV-2 U.K. Strain Spike Protein in Cell Culture | Pfizer https://t.co/YXcSnjLt8C"}, {"id": "1400821856362401792", "text": "Pfizer-BioNTech's covid-19 vaccine elicits lower levels of antibodies against the SARS-CoV-2\u00a0Delta variant\u00a0(B.1.617.2), first discovered in India, in comparison to other variants, said a research published in\u00a0Lancet\u00a0journal.\n https://t.co/IaCMX81X3b"}, {"id": "1367252963190665219", "text": "New research from UNC-Chapel Hill suggests that those who have previously experienced a SARS-CoV-2 infection develop a significant antibody response to the first dose of mRNA-based COVID-19 vaccine.\nhttps://t.co/B4vR1KUQ0w"}, {"id": "1375949502461394946", "text": "Mechanism of a COVID-19 nanoparticle vaccine candidate that elicits a broadly neutralizing antibody response to SARS-CoV-2 variants https://t.co/nc1L0uvtlI #bioRxiv"}, {"id": "1395428608349548550", "text": "JCI - Efficient maternal to neonatal transfer of antibodies against SARS-CoV-2 and BNT162b2 mRNA COVID-19 vaccine https://t.co/vIBcpPaKFZ"}], "summary": "The COVID-19 vaccine appears to be effective against the novel, rapidly spreading variants of SARS-CoV-2. Pfizer-BioNTech's COVID-19 vaccine use small portion of the viral sequence of the SARS-CoV-2 virus to equip the body with the ability to fight the virus better in case you get it."}
Data Fields
{'id': text of paper abstract
'docs': document id
[
'id': id of text
'text': text data
]
'summary': summary text
}
Data Splits
The data is split into a training, validation and test.
| train | validation | test |
|---|---|---|
| 50 | 10 | 5 |
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[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
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
@article{lu2020multi,
title={Multi-Document: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles},
author={Arka Das, India},
journal={arXiv preprint arXiv:2010.14235},
year={2022}
}
Contributions
Thanks to [@arka0821] (https://github.com/arka0821/multi_document_summarization) for adding this dataset.
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