| spacy-test | | Random set of articles used for testing in the development of the RESTful spaCy parsing web service. Since development is now finished, they are released for the community to use. | 131 K | Nico Colic | Nico Colic | 2023-11-29 | Released | |
| bionlp-st-id-2011-training | | The training dataset from the infectious diseases (ID) task in the BioNLP Shared Task 2011.
Entity types: - Genes and gene products: gene, RNA, and protein name mentions. - Two-component systems: mentions of the names of two-component regulatory systems, frequently embedding the names of the two Proteins forming the system.- Chemicals: mentions of chemical compounds such as "NaCL".- Organisms: mentions of organism names or organism specification through specific properties (e.g. "graRS mutant").- Regulons/Operons: mentions of names of specific regulons and operons. | 5.61 K | University of Tokyo Tsujii Laboratory, NaCTeM and Biocomplexity Institute of Virginia Tech | Yue Wang | 2023-11-28 | Released | |
| pubmed-sentences-benchmark | | A benchmark data for text segmentation into sentences.
The source of annotation is the GENIA treebank v1.0.
Following is the process taken.
began with the GENIA treebank v1.0.
sentence annotations were extracted and converted to PubAnnotation JSON.
uploaded. 12 abstracts met alignment failure.
among the 12 failure cases, 4 had a dot('.') character where there should be colon (':'). They were manually fixed then successfully uploaded: 7903907, 8053950, 8508358, 9415639.
among the 12 failed abstracts, 8 were "250 word truncation" cases. They were manually fixed and successfully uploaded. During the fixing, manual annotations were added for the missing pieces of text.
30 abstracts had extra text in the end, indicating copyright statement, e.g., "Copyright 1998 Academic Press." They were annotated as a sentence in GTB. However, the text did not exist anymore in PubMed. Therefore, the extra texts were removed, together with the sentence annotation to them.
| 18.4 K | GENIA project | Jin-Dong Kim | 2023-11-28 | Released | |
| bionlp-st-cg-2013-training | | The training dataset from the cancer genetics task in the BioNLP Shared Task 2013.
Composed of anatomical and molecular entities. | 10.9 K | NaCTeM | Yue Wang | 2023-11-28 | Released | |
| bionlp-st-2016-SeeDev-training | | Entities and event annotations from the training set of the BioNLP-ST 2016 SeeDev task.
SeeDev task focuses on seed storage and reserve accumulation on the model organism, Arabidopsis thaliana. The SeeDev task is based on the knowledge model Gene Regulation Network for Arabidopsis (GRNA) that meets the needs of text-mining (i.e. manual annotation of texts and automatic information extraction), experimental data indexing and retrieval and reuse in other plant systems. It is also expected to meet the requirements of the integration of the text knowledge with knowledge derived from experimental data in view of modeling in systems biology.
GRNA model defines 16 different types of entities, and 22 types of event (in five sets of event types) that may be combined in complex events.
For more information, please refer to the task website
All annotations :
Train set
Development set
Test set (without events)
| 35 | | EstelleChaix | 2023-11-28 | Released | |
| SPECIES800 | | SPECIES 800 (S800): an abstract-based manually annotated corpus. S800 comprises 800 PubMed abstracts in which organism mentions were identified and mapped to the corresponding NCBI Taxonomy identifiers.
Described in:
The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text.
Pafilis E, Frankild SP, Fanini L, Faulwetter S, Pavloudi C, et al. (2013). PLoS ONE, 2013, 8(6): e65390. doi:10.1371/journal.pone.0065390 | 3.71 K | Evangelos Pafilis, Sune P. Frankild, Lucia Fanini, Sarah Faulwetter, Christina Pavloudi, Aikaterini Vasileiadou, Christos Arvanitidis, Lars Juhl Jensen | evangelos | 2023-11-28 | Released | |
| PubMed_Structured_Abstracts | | Sections (zones) as retrieved from PubMed. | 131 K | | zebet | 2023-11-28 | Released | |
| 2015-BEL-Sample-2 | | The 295 BEL statements for sample set used for the 2015 BioCreative challenge. | 11.4 K | Fabio Rinaldi | Nico Colic | 2023-11-28 | Released | |
| SMAFIRA_Feedback_Research_Goal | | | 15 | | zebet | 2023-11-28 | Released | |
| LitCovid-OGER-BB | | Using OGER (www.ontogene.com) and Biobert to obtain annotations for 10 different vocabularies. | 308 K | Fabio Rinaldi | Nico Colic | 2023-11-28 | Released | |
| SCAI-Test | | A small corpus for the evaluation of dictionaries containing chemical entities.
Publication: http://www.scai.fraunhofer.de/fileadmin/images/bio/data_mining/paper/kolarik2008.pdf
Original source: https://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads/corpora-for-chemical-entity-recognition.html | 1.21 K | CALBC Project | Yue Wang | 2023-11-28 | Released | |
| CellFinder | | CellFinder corpus | 4.75 K | Mariana Neves, Alexander Damaschun, Andreas Kurtz, Ulf Leser | Mariana Neves | 2023-11-27 | Released | |
| 123123123 | | 123123123 | 150 | | yaoxinzhi | 2023-11-27 | Released | |
| PIR-corpus1 | | The Protein Information Resource (PIR) is not biased towards any particular biomedical domain, and is expected to provide more diverse protein names in a given sample size.
Annotation category: protein, compound-protein, acronym. | 4.44 K | University of Delaware and Georgetown University Medical Center | Yue Wang | 2023-11-27 | Released | |
| LitCovid-sentences-v1 | | Sentence segmentation of all the texts in the LitCovid literature. The segmentation is automatically obtained using the TextSentencer annotation service developed and maintained by DBCLS. | 16.5 K | | Jin-Dong Kim | 2023-11-27 | Released | |
| Zoonoses_partialAnnotation | | This is a part of Zoonoses project used by PanZoora. But Zoonoses project provides whole manual annotated data but this is partial ones. | 266 | | AikoHIRAKI | 2023-11-27 | Released | |
| bionlp-st-ge-2016-test-proteins | | Protein annotations to the benchmark test data set of the BioNLP-ST 2016 GE task.
A participant of the GE task may import the documents and annotations of this project to his/her own project, to begin with producing event annotations.
For more details, please refer to the benchmark test data set (bionlp-st-ge-2016-test).
| 4.34 K | DBCLS | Jin-Dong Kim | 2023-11-27 | Released | |
| bionlp-st-pc-2013-training | | The training dataset from the pathway curation (PC) task in the BioNLP Shared Task 2013.
The entity types defined in the PC task are simple chemical, gene or gene product, complex and cellular component. | 7.86 K | NaCTeM and KISTI | Yue Wang | 2023-11-27 | Released | |
| craft-sa-dev | | Development data for CRAFT SA shared task. This project contains the development (training) annotations for the Structural Annotation task of the CRAFT Shared Task 2019. This particular set contains token and sentence annotations with tokens linked via dependency relations. These dependency relations were automatically generated using the manually curated CRAFT constituency treebank files as input. | 490 K | University of Colorado Anschutz Medical Campus | craft-st | 2023-11-27 | Released | |
| LitCovid-PubTatorCentral | | Named-entities for the documents in the LitCovid dataset. Annotations were automatically predicted by the PubTatorCentral tool (https://www.ncbi.nlm.nih.gov/research/pubtator/) | 4.64 K | | zebet | 2023-11-27 | Released | |
