The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 82, in _split_generators
raise ValueError(
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PubTator3 Tagger (Offline Package)
This dataset provides the complete PubTator3 offline tagger package, distributed as a multi-part compressed archive for large-scale biomedical text mining.
The package supports batch annotation of PubMed / PMC-scale corpora and is intended for research use only.
Package Distribution
The tagger is distributed as multiple compressed files:
PubTator3_tagger.tar.gz.part_*
All parts must be downloaded and placed in the same directory before reconstruction.
Installation
1. Reconstruct the archive
bash cat PubTator3_tagger.tar.gz.part_* > PubTator3_tagger.tar.gz
2. Extract the package
bash tar -xzf PubTator3_tagger.tar.gz
After extraction, a directory named 'PubTator3_tagger/' will be created, containing all required files and scripts.
3. Install required dependencies
bash ./Installation.sh
▶️ Usage
Detailed usage instructions are provided inside the extracted 'PubTator3_tagger/' directory.
Input locations
Free-text input:
${DIR}/Data/input_txt
BioC XML format:
${DIR}/Data/input_bioc
Run the batch tagging pipeline
bash ./PubTator.sh
Intended Use
These tools are intended for research use in biomedical text mining and natural language processing, including large-scale literature annotation and information extraction.
This repository does not provide an online inference API.
Disclaimer
This research was supported by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.
Citation
Please cite the relevant publications below.
- Wei C-H, Allot A, Lai P-T, Leaman R, Tian S, Luo L, Jin Q, Wang Z, Chen Q, Lu Z. PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge. Nucleic Acids Research. 2024;51(W1):W540–W546.
Taggers
Taggers of PubTator3 are listed below.
- Wei C-H, Luo L, Islamaj R, Lai P-T, Lu Z. GNorm2: an improved gene name recognition and normalization system. Bioinformatics. 2023;39(10):btad599.
- Wei C-H, Allot A, Riehle K, Milosavljevic A, Lu Z. tmVar 3.0: an improved variant concept recognition and normalization tool. Bioinformatics. 2022;38(18):4449–4451.
- Lai P-T, Wei C-H, Tian S, Leaman R, Lu Z. Enhancing Biomedical Relation Extraction with Directionality. Bioinformatics. 2025;41(Supplement_1):i68–i76.
- Islamaj R, Leaman R, Kim S, Kwon D, Wei C-H, Comeau DC, Peng Y, Cissel D, Coss C, Fisher C, Guzman R, Kochar PG, Koppel S, Trinh D, Sekiya K, Ward J, Whitman D, Schmidt S, Lu Z. NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature. Scientific Data. 2021;8(1):91.
- Leaman R, Lu Z. TaggerOne: joint named entity recognition and normalization with semi-Markov Models. Bioinformatics. 2016;32(18):2839–2846.
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