multilinguality:monolingual language:en license:unknown region:us
The task focuses on the extraction of the locations and phenotypes of
microorganisms from PubMed abstracts and full-text excerpts, and the
characterization of these entities with respect to reference knowledge
sources (NCBI taxonomy, OntoBiotope ontology). The task is motivated by
the importance of the knowledge on biodiversity for fundamental research
and applications in microbiology.
@inproceedings{bossy-etal-2019-bacteria,
    title = "Bacteria Biotope at {B}io{NLP} Open Shared Tasks 2019",
    author = "Bossy, Robert  and
      Del{\'e}ger, Louise  and
      Chaix, Estelle  and
      Ba, Mouhamadou  and
      N{\'e}dellec, Claire",
    booktitle = "Proceedings of The 5th Workshop on BioNLP Open Shared Tasks",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/D19-5719",
    doi = "10.18653/v1/D19-5719",
    pages = "121--131",
    abstract = "This paper presents the fourth edition of the Bacteria
    Biotope task at BioNLP Open Shared Tasks 2019. The task focuses on
    the extraction of the locations and phenotypes of microorganisms
    from PubMed abstracts and full-text excerpts, and the characterization
    of these entities with respect to reference knowledge sources (NCBI
    taxonomy, OntoBiotope ontology). The task is motivated by the importance
    of the knowledge on biodiversity for fundamental research and applications
    in microbiology. The paper describes the different proposed subtasks, the
    corpus characteristics, and the challenge organization. We also provide an
    analysis of the results obtained by participants, and inspect the evolution
    of the results since the last edition in 2016.",
}

---
language: 
- en
bigbio_language: 
- English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: BioNLP 2019 BB
homepage: https://sites.google.com/view/bb-2019/dataset
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks: 
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISAMBIGUATION
- RELATION_EXTRACTION
---


# Dataset Card for BioNLP 2019 BB

## Dataset Description

- **Homepage:** https://sites.google.com/view/bb-2019/dataset
- **Pubmed:** True
- **Public:** True
- **Tasks:** NER,NED,RE


The task focuses on the extraction of the locations and phenotypes of
microorganisms from PubMed abstracts and full-text excerpts, and the
characterization of these entities with respect to reference knowledge
sources (NCBI taxonomy, OntoBiotope ontology). The task is motivated by
the importance of the knowledge on biodiversity for fundamental research
and applications in microbiology.




## Citation Information

```
@inproceedings{bossy-etal-2019-bacteria,
    title = "Bacteria Biotope at {B}io{NLP} Open Shared Tasks 2019",
    author = "Bossy, Robert  and
      Del{'e}ger, Louise  and
      Chaix, Estelle  and
      Ba, Mouhamadou  and
      N{'e}dellec, Claire",
    booktitle = "Proceedings of The 5th Workshop on BioNLP Open Shared Tasks",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/D19-5719",
    doi = "10.18653/v1/D19-5719",
    pages = "121--131",
    abstract = "This paper presents the fourth edition of the Bacteria
    Biotope task at BioNLP Open Shared Tasks 2019. The task focuses on
    the extraction of the locations and phenotypes of microorganisms
    from PubMed abstracts and full-text excerpts, and the characterization
    of these entities with respect to reference knowledge sources (NCBI
    taxonomy, OntoBiotope ontology). The task is motivated by the importance
    of the knowledge on biodiversity for fundamental research and applications
    in microbiology. The paper describes the different proposed subtasks, the
    corpus characteristics, and the challenge organization. We also provide an
    analysis of the results obtained by participants, and inspect the evolution
    of the results since the last edition in 2016.",
}

```
