---
language: 
- en
bigbio_language: 
- English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: PICO Annotation
homepage: https://github.com/Markus-Zlabinger/pico-annotation
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks: 
- NAMED_ENTITY_RECOGNITION
---


# Dataset Card for PICO Annotation

## Dataset Description

- **Homepage:** https://github.com/Markus-Zlabinger/pico-annotation
- **Pubmed:** True
- **Public:** True
- **Tasks:** NER


This dataset contains annotations for Participants, Interventions, and Outcomes (referred to as PICO task).
For 423 sentences, annotations collected by 3 medical experts are available.
To get the final annotations, we perform the majority voting.



## Citation Information

```
@inproceedings{zlabinger-etal-2020-effective,
    title = "Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports",
    author = {Zlabinger, Markus  and
      Sabou, Marta  and
      Hofst{"a}tter, Sebastian  and
      Hanbury, Allan},
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.findings-emnlp.274",
    doi = "10.18653/v1/2020.findings-emnlp.274",
    pages = "3064--3074",
}

```