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Original work titled: 'Binding and Flip as Initial Steps for BP-100 Antimicrobial Actions' (Scientific Reports/Nature Publishing Group UK) by the following authors: Peter Park; Leandro R. Franco; Hernan Chaimovich; Kaline Coutinho; Iolanda M. Cuccovia; Filipe S. Lima DOI: 10.1038/s41598-019-45075-5 | 5388809896c7b2a9adf5d708f6ea4b08 | CC-BY | http://creativecommons.org/licenses/by/4.0/ | 4.0 | [
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End of preview. Expand
in Data Studio
Dataset Summary
TEA – Pathogen Identifier and Strain Tagger is a curated biomedical corpus comprising:
- 505 full-text articles curated for human microbial pathogens
- 400 articles focused on microbial strains
The dataset includes over 3,500 entity spans annotated in IOB2 format.
Licensing
All examples in the main branch (i.e. inside all/species/strains/raw subsets) are released under the CC BY license.
For a small number of additional examples available under other CC licenses, please refer to the all-data branch.
Usage
from datasets import load_dataset
# Load augmented versions
pathogens_ds = load_dataset("tznurmin/tea_curated", "pathogens-all", split="train")
strains_ds = load_dataset("tznurmin/tea_curated", "strains-species", split="train")
print(pathogens_ds[1589])
print(len(strains_ds))
For development or regenerating augmentations, you can use the dyn-aug branch:
Clone the dataset repository
git clone https://huggingface.co/datasets/tznurmin/tea_curated
cd tea_curated
git checkout dyn-aug
# Install lfs if needed
git lfs install
# Pull the data files
git lfs pull
Install dependencies
# Optional but recommended
python -m venv .venv
# On Windows: .venv\Scripts\activate
source .venv/bin/activate
# Install the required packages
pip install datasets transformers # or use requirements.txt
# TEA handles augmentation
pip install 'git+https://github.com/tznurmin/TEA.git@main#egg=tea'
Usage
from datasets import load_dataset
pathogens_ds = load_dataset("tea_curated.py", "pathogens-all", split="train", trust_remote_code=True)
strains_ds = load_dataset("tea_curated.py", "strains-all", split="train", trust_remote_code=True)
print(pathogens_ds[1589])
print(len(strains_ds))
More information
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