
**Official website**: https://github.com/lfoppiano/SuperMat

### Reference

The paper discussing this datset can be found [here](https://doi.org/10.1080/27660400.2021.1918396) or on [arxiv](arxiv.org/abs/2101.02455)

For citing: 
```
@article{doi:10.1080/27660400.2021.1918396,
author = {Luca Foppiano and Sae Dieb and Akira Suzuki and Pedro Baptista de Castro and Suguru Iwasaki and Azusa Uzuki and Miren Garbine Esparza Echevarria and Yan Meng and Kensei Terashima and Laurent Romary and Yoshihiko Takano and Masashi Ishii},
title = {SuperMat: construction of a linked annotated dataset from superconductors-related publications},
journal = {Science and Technology of Advanced Materials: Methods},
volume = {1},
number = {1},
pages = {34-44},
year  = {2021},
publisher = {Taylor & Francis},
doi = {10.1080/27660400.2021.1918396},

URL = { 
        https://doi.org/10.1080/27660400.2021.1918396
    
},
eprint = { 
        https://doi.org/10.1080/27660400.2021.1918396
    
}

}
```
task_categories:token-classification size_categories:1M<n<10M language:en license:cc-by-4.0 materials science ner machine learning superconductors arxiv:2101.02455 region:us
{"language": ["en"], "license": "cc-by-4.0", "size_categories": ["1M<n<10M"], "task_categories": ["token-classification"], "pretty_name": "supermat", "tags": ["materials science", "ner", "machine learning", "superconductors"]}
TAGS
#task_categories-token-classification #size_categories-1M<n<10M #language-English #license-cc-by-4.0 #materials science #ner #machine learning #superconductors #arxiv-2101.02455 #region-us 


Official website: URL

### Reference

The paper discussing this datset can be found here or on arxiv

For citing: 

### Reference

The paper discussing this datset can be found here or on arxiv

For citing:
TAGS
#task_categories-token-classification #size_categories-1M<n<10M #language-English #license-cc-by-4.0 #materials science #ner #machine learning #superconductors #arxiv-2101.02455 #region-us 
 ### Reference

The paper discussing this datset can be found here or on arxiv

For citing: