|
|
--- |
|
|
dataset_info: |
|
|
- config_name: '16384' |
|
|
features: |
|
|
- name: input |
|
|
dtype: string |
|
|
- name: output |
|
|
dtype: string |
|
|
- name: metadata |
|
|
struct: |
|
|
- name: domains |
|
|
sequence: string |
|
|
- name: input_context |
|
|
dtype: string |
|
|
- name: output_context |
|
|
dtype: string |
|
|
- name: source_type |
|
|
dtype: string |
|
|
- name: task_family |
|
|
dtype: string |
|
|
- name: _instance_id |
|
|
dtype: string |
|
|
splits: |
|
|
- name: train |
|
|
num_bytes: 651887545 |
|
|
num_examples: 72646 |
|
|
- name: validation |
|
|
num_bytes: 316306085 |
|
|
num_examples: 34621 |
|
|
- name: test |
|
|
num_bytes: 422473879 |
|
|
num_examples: 41909 |
|
|
download_size: 623896235 |
|
|
dataset_size: 1390667509 |
|
|
- config_name: '4096' |
|
|
features: |
|
|
- name: input |
|
|
dtype: string |
|
|
- name: output |
|
|
dtype: string |
|
|
- name: metadata |
|
|
struct: |
|
|
- name: domains |
|
|
sequence: string |
|
|
- name: input_context |
|
|
dtype: string |
|
|
- name: output_context |
|
|
dtype: string |
|
|
- name: source_type |
|
|
dtype: string |
|
|
- name: task_family |
|
|
dtype: string |
|
|
- name: _instance_id |
|
|
dtype: string |
|
|
splits: |
|
|
- name: train |
|
|
num_bytes: 388072842 |
|
|
num_examples: 70521 |
|
|
- name: validation |
|
|
num_bytes: 147030710 |
|
|
num_examples: 30736 |
|
|
- name: test |
|
|
num_bytes: 186329809 |
|
|
num_examples: 35875 |
|
|
download_size: 308815650 |
|
|
dataset_size: 721433361 |
|
|
- config_name: '8192' |
|
|
features: |
|
|
- name: input |
|
|
dtype: string |
|
|
- name: output |
|
|
dtype: string |
|
|
- name: metadata |
|
|
struct: |
|
|
- name: domains |
|
|
sequence: string |
|
|
- name: input_context |
|
|
dtype: string |
|
|
- name: output_context |
|
|
dtype: string |
|
|
- name: source_type |
|
|
dtype: string |
|
|
- name: task_family |
|
|
dtype: string |
|
|
- name: _instance_id |
|
|
dtype: string |
|
|
splits: |
|
|
- name: train |
|
|
num_bytes: 546901470 |
|
|
num_examples: 72367 |
|
|
- name: validation |
|
|
num_bytes: 252982177 |
|
|
num_examples: 34001 |
|
|
- name: test |
|
|
num_bytes: 313157272 |
|
|
num_examples: 40064 |
|
|
download_size: 491399393 |
|
|
dataset_size: 1113040919 |
|
|
configs: |
|
|
- config_name: '16384' |
|
|
data_files: |
|
|
- split: train |
|
|
path: 16384/train-* |
|
|
- split: validation |
|
|
path: 16384/validation-* |
|
|
- split: test |
|
|
path: 16384/test-* |
|
|
- config_name: '4096' |
|
|
data_files: |
|
|
- split: train |
|
|
path: 4096/train-* |
|
|
- split: validation |
|
|
path: 4096/validation-* |
|
|
- split: test |
|
|
path: 4096/test-* |
|
|
- config_name: '8192' |
|
|
data_files: |
|
|
- split: train |
|
|
path: 8192/train-* |
|
|
- split: validation |
|
|
path: 8192/validation-* |
|
|
- split: test |
|
|
path: 8192/test-* |
|
|
license: odc-by |
|
|
language: |
|
|
- en |
|
|
tags: |
|
|
- chemistry |
|
|
- biomedicine |
|
|
- clinical medicine |
|
|
- artificial intelligence |
|
|
- materials science |
|
|
size_categories: |
|
|
- 100K<n<1M |
|
|
--- |
|
|
# SciRIFF |
|
|
|
|
|
The SciRIFF dataset includes 137K instruction-following demonstrations for 54 scientific literature understanding tasks. The tasks cover five essential scientific literature categories and span five domains. |
|
|
|
|
|
## License |
|
|
|
|
|
SciRIFF is licensed under `ODC-By`. |
|
|
|
|
|
## Task provenance |
|
|
|
|
|
SciRIFF was created by repurposing existing scientific literature understanding datasets. Below we provide information on the source data for each SciRIFF task, including license information on individual datasets where available. |
|
|
|
|
|
| SciRIFF Name | Paper Link | License | Website / Download Link | |
|
|
| :---------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------- | :----------------------------------------------------------------------------------------- | |
|
|
| `acl_arc_intent_classification` | [ACL ARC](https://aclanthology.org/L08-1005/) | - | <https://github.com/allenai/scicite/> | |
|
|
| `anat_em_ner` | [AnatEM](https://academic.oup.com/bioinformatics/article/30/6/868/285282) | CC BY | <https://nactem.ac.uk/anatomytagger/#AnatEM> | |
|
|
| `annotated_materials_syntheses_events` | [Materials Science Procedural Text Corpus](https://aclanthology.org/W19-4007/) | MIT | <https://github.com/olivettigroup/annotated-materials-syntheses> | |
|
|
| `bc7_litcovid_topic_classification` | [BioCreative VII LitCOVID](https://pubmed.ncbi.nlm.nih.gov/36043400/) | - | <https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-5/> | |
|
|
| `bioasq_{factoid,general,list,yesno}_qa` | [BioASQ](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0564-6) | CC BY | <http://bioasq.org/> | |
|
|
| `biored_ner` | [BioRED](https://academic.oup.com/bib/article/23/5/bbac282/6645993) | - | <https://ftp.ncbi.nlm.nih.gov/pub/lu/BioRED/> | |
|
|
| `cdr_ner` | [BioCreative V CDR](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4860626/) | - | <https://biocreative.bioinformatics.udel.edu/tasks/biocreative-v/track-3-cdr/> | |
|
|
| `chemdner_ner` | [CHEMDNER](https://jcheminf.biomedcentral.com/articles/10.1186/1758-2946-7-S1-S2) | - | <https://biocreative.bioinformatics.udel.edu/resources/biocreative-iv/chemdner-corpus/> | |
|
|
| `chemprot_{ner,re}` | [BioCreative VI ChemProt](https://www.semanticscholar.org/paper/Overview-of-the-BioCreative-VI-chemical-protein-Krallinger-Rabal/eed781f498b563df5a9e8a241c67d63dd1d92ad5) | - | <https://biocreative.bioinformatics.udel.edu/news/corpora/chemprot-corpus-biocreative-vi/> | |
|
|
| `chemsum_single_document_summarization` | [ChemSum](https://aclanthology.org/2023.acl-long.587/) | - | <https://github.com/griff4692/calibrating-summaries> | |
|
|
| `chemtables_te` | [ChemTables](https://arxiv.org/abs/2305.14336) | GPL 3.0 | <https://huggingface.co/datasets/fbaigt/schema-to-json> | |
|
|
| `chia_ner` | [Chia](https://www.nature.com/articles/s41597-020-00620-0) | CC BY | <https://github.com/WengLab-InformaticsResearch/CHIA> | |
|
|
| `covid_deepset_qa` | [COVID-QA](https://aclanthology.org/2020.nlpcovid19-acl.18/) | Apache 2.0 | <https://github.com/deepset-ai/COVID-QA> | |
|
|
| `covidfact_entailment` | [CovidFact](https://aclanthology.org/2021.acl-long.165/) | - | <https://github.com/asaakyan/covidfact> | |
|
|
| `craftchem_ner` | [CRAFT-Chem](https://link.springer.com/chapter/10.1007/978-94-024-0881-2_53) | - | <https://huggingface.co/datasets/ghadeermobasher/CRAFT-Chem> | |
|
|
| `data_reco_mcq_{mc,sc}` | [DataFinder](https://aclanthology.org/2023.acl-long.573/) | Apache 2.0 | <https://github.com/viswavi/datafinder/tree/main> | |
|
|
| `ddi_ner` | [DDI](https://www.sciencedirect.com/science/article/pii/S1532046413001123) | CC BY | <https://github.com/isegura/DDICorpus> | |
|
|
| `discomat_te` | [DISCoMaT](https://aclanthology.org/2023.acl-long.753/) | CC BY-SA | <https://github.com/M3RG-IITD/DiSCoMaT> | |
|
|
| `drug_combo_extraction_re` | [Drug Combinations](https://aclanthology.org/2022.naacl-main.233/) | - | <https://github.com/allenai/drug-combo-extraction> | |
|
|
| `evidence_inference` | [Evidence inference](https://aclanthology.org/2020.bionlp-1.13/) | MIT | <https://evidence-inference.ebm-nlp.com/> | |
|
|
| `genia_ner` | [JNLPBA](https://aclanthology.org/W04-1213/) | CC BY | <https://github.com/spyysalo/jnlpba> | |
|
|
| `gnormplus_ner` | [GNormPlus](https://www.hindawi.com/journals/bmri/2015/918710/) | - | <https://www.ncbi.nlm.nih.gov/research/bionlp/Tools/gnormplus/> | |
|
|
| `healthver_entailment` | [HealthVer](https://aclanthology.org/2021.findings-emnlp.297/) | nan | <https://github.com/sarrouti/healthver> | |
|
|
| `linnaeus_ner` | [LINNAEUS](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-85) | CC BY | <https://sourceforge.net/projects/linnaeus/> | |
|
|
| `medmentions_ner` | [MedMentions](https://arxiv.org/abs/1902.09476) | CC 0 | <https://github.com/chanzuckerberg/MedMentions> | |
|
|
| `mltables_te` | [AxCell](https://aclanthology.org/2020.emnlp-main.692/) | Apache 2.0 | <https://github.com/paperswithcode/axcell> | |
|
|
| `mslr2022_cochrane_multidoc_summarization` | [Cochrane](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378607/) | Apache 2.0 | <https://github.com/allenai/mslr-shared-task> | |
|
|
| `mslr2022_ms2_multidoc_summarization` | [MS^2](https://aclanthology.org/2021.emnlp-main.594/) | Apache 2.0 | <https://github.com/allenai/mslr-shared-task> | |
|
|
| `multicite_intent_classification` | [MultiCite](https://aclanthology.org/2022.naacl-main.137/) | CC BY-NC | <https://github.com/allenai/multicite> | |
|
|
| `multixscience_multidoc_summarization` | [Multi-XScience](https://aclanthology.org/2020.emnlp-main.648/) | MIT | <https://github.com/yaolu/Multi-XScience> | |
|
|
| `mup_single_document_summarization` | [MUP](https://aclanthology.org/2022.sdp-1.32/) | Apache 2.0 | <https://github.com/allenai/mup> | |
|
|
| `ncbi_ner` | [NCBI Disease](https://pubmed.ncbi.nlm.nih.gov/24393765/) | CC 0 | <https://www.ncbi.nlm.nih.gov/CBBresearch/Dogan/DISEASE/> | |
|
|
| `nlmchem_ner` | [NLM-Chem](https://pubmed.ncbi.nlm.nih.gov/33767203/) | CC 0 | <https://ftp.ncbi.nlm.nih.gov/pub/lu/BC7-NLM-Chem-track/> | |
|
|
| `nlmgene_ner` | [NLM-Gene](https://pubmed.ncbi.nlm.nih.gov/33839304/) | CC 0 | <https://ftp.ncbi.nlm.nih.gov/pub/lu/NLMGene/> | |
|
|
| `pico_ner` | [EBM-NLP PICO](https://aclanthology.org/P18-1019/) | - | <https://github.com/bepnye/EBM-NLP> | |
|
|
| `pubmedqa_qa` | [PubMedQA](https://aclanthology.org/D19-1259/) | MIT | <https://github.com/pubmedqa/pubmedqa> | |
|
|
| `qasa_abstractive_qa` | [QASA](https://proceedings.mlr.press/v202/lee23n) | MIT | <https://github.com/lgresearch/QASA> | |
|
|
| `qasper_{abstractive,extractive}_qa` | [Qasper](https://aclanthology.org/2021.naacl-main.365/) | CC BY | <https://allenai.org/data/qasper> | |
|
|
| `scicite_classification` | [SciCite](https://aclanthology.org/N19-1361/) | - | <https://allenai.org/data/scicite> | |
|
|
| `scientific_lay_summarisation_`<br>`{elife,plos}_single_doc_summ` | [Lay Summarisation](https://aclanthology.org/2022.emnlp-main.724/) | - | <https://github.com/TGoldsack1/Corpora_for_Lay_Summarisation> | |
|
|
| `scientific_papers_summarization_`<br>`single_doc_{arxiv,pubmed}` | [Scientific Papers](https://aclanthology.org/N18-2097/) | - | <https://huggingface.co/datasets/armanc/scientific_papers> | |
|
|
| `scierc_{ner,re}` | [SciERC](https://aclanthology.org/D18-1360/) | - | <http://nlp.cs.washington.edu/sciIE/> | |
|
|
| `scifact_entailment` | [SciFact](https://aclanthology.org/2020.emnlp-main.609/) | CC BY-NC | <https://allenai.org/data/scifact> | |
|
|
| `scireviewgen_multidoc_summarization` | [SciReviewGen](https://aclanthology.org/2023.findings-acl.418/) | CC BY-NC | <https://github.com/tetsu9923/SciReviewGen> | |
|
|
| `scitldr_aic` | [SciTLDR](https://aclanthology.org/2020.findings-emnlp.428/) | Apache 2.0 | <https://github.com/allenai/scitldr> | |
|
|
|