task_categories:question-answering task_categories:token-classification language:en license:cc-by-nc-sa-4.0 size_categories:n<1K format:json modality:text library:datasets library:pandas library:mlcroissant library:polars doi:10.57967/hf/1011 region:us
---
license: cc-by-nc-sa-4.0
task_categories:
- question-answering
- token-classification
language:
- en
pretty_name: Named Entity Recognition of funders of scientific research
size_categories:
- n<1K
---
# Dataset Card for Dataset Named Entity Recognition of funders of scientific research

## Dataset Description

- **Homepage:https://econstor.eu** 
- **Repository:https://github.com/zbw/Funder-NER** 
- **Paper: https://doi.org/10.1007/978-3-031-16802-4_24** 
- **Leaderboard:** 
- **Point of Contact:** 

### Dataset Summary

Training/test set for automatically identifying funder entities mentioned in scientific papers. This data set is generated from Open Access documents hosted at https://econstor.eu and manually curated/labeled.

### Supported Tasks and Leaderboards

The dataset is for training and testing the automatic recognition of funders as they are acknowledged in scientific papers.

### Languages

English

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

"handle: the PID of the OA working paper"
"crossref_doi: the PID of the corresponding publication (article), as registered via CrossRef"
"crossref_phrase: the funder according to CrossRef metadata"
"pdf_phrase: the acknowledgement phrase from the paper"
"funder: Y(es) in case there is at least one funder, N(o) in case there is no funder supporting the work, but OA publishing funding"

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

The dataset was manually curated to train the NER recognition based on a QA system.

### 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

[More Information Needed]

### Contributions

[More Information Needed]