| bionlp-ost-19-BB-kb-ner-train | | | 3.56 K | | ldeleger | 2023-11-28 | Developing | |
| bionlp-ost-19-BB-kb-ner-test | | | 125 | | ldeleger | 2023-11-28 | Developing | |
| bionlp-ost-19-BB-kb-ner-dev | | | 1.9 K | | ldeleger | 2023-11-29 | Developing | |
| bionlp-ost-19-BB-kb-dev | | | 1.89 K | | ldeleger | 2023-11-26 | Developing | |
| BioNLP16_Messiy | | | 6.5 K | | Messiy | 2023-11-29 | Testing | |
| BioNLP16_DUT | | | 6.5 K | | Messiy | 2023-11-29 | Testing | |
| BioMedLAT | | Annotation of 643 questions from BioASQ with the Lexical Answer Type (LAT) and headword. | 0 | | | 2016-09-23 | Developing | |
| biomarkers | | IL/TNF biomarkers | 857 K | | alo33 | 2023-11-24 | | |
| BioLarkPubmedHPO | | 228 abstracts manually annotated with Human Phenotype Ontology (HPO) concepts and harmonized by three curators, which can be used as a reference standard for free text annotation of human phenotypes. For more info, please see Groza et al. "Automatic concept recognition using the human phenotype ontology reference and test suite corpora", 2015. | 7.16 K | Tudor Groza | simon | 2023-11-29 | Released | |
| Bioinformatics_fulltext | | | 0 | | Sophie Nam | 2023-11-28 | Uploading | |
| BioASQ-sample | | collection of PubMed articles which appear in the BioASQ sample data set. | 0 | BioASQ | Jin-Dong Kim | 2023-11-28 | Testing | |
| bc2gn_test | | test | 0 | | | 2021-07-13 | Testing | |
| bayaba | | nalee | 7 | | Nakyolee | 2023-11-29 | | |
| AxD_symptoms | | Symptoms of AxD from available case report and case series | 401 | | Eisuke Dohi | 2023-11-29 | Developing | |
| ASCO_abstracts | | asco abstracts sample dataset | 28 K | | alo33 | 2023-11-29 | Testing | |
| Annotation-Euglena-Enzymes | | | 0 | | Shuichi Kawashima | 2016-06-13 | Developing | |
| AnEM_full-texts | | 250 documents selected randomly from full-text papers
Entity types: organism subdivision, anatomical system, organ, multi-tissue structure, tissue, cell, developing anatomical structure, cellular component, organism substance, immaterial anatomical entity and pathological formation
Together with AnEM_abstracts, it is probably the largest manually annotated corpus on anatomical entities. | 687 | NaCTeM | Yue Wang | 2023-11-29 | Uploading | |
| AnEM_abstracts | | 250 documents selected randomly from citation abstracts
Entity types: organism subdivision, anatomical system, organ, multi-tissue structure, tissue, cell, developing anatomical structure, cellular component, organism substance, immaterial anatomical entity and pathological formation
Together with AnEM_full-texts, it is probably the largest manually annotated corpus on anatomical entities. | 1.91 K | NaCTeM | Yue Wang | 2023-11-29 | Released | |
| American_Journal | | | 0 | | Sophie Nam | 2023-11-29 | | |
| AlvisNLP-Test | | Project for testing AlviNLP PubAnnotation server during BLAH3. | 17 | | Bibliome | 2023-11-29 | Testing | |
