| korean_corpus_dep | | | 0 | | donghwan kim | 2019-04-23 | | |
| NER-microbes | | | 10 | | Shuichi Kawashima | 2023-11-29 | Developing | |
| SMAFIRA_Feedback_Labels | | | 0 | | zebet | 2021-01-21 | Developing | |
| Glycobiology-GlycanName | | | 946 | Toshihide Shikanai | shikanai | 2023-11-27 | Testing | |
| Training_Data_Japanese_ja_en | | | 0 | | wmtbio | 2023-11-27 | Developing | |
| korean_corpus_pos | | | 0 | | donghwan kim | 2023-11-27 | | |
| 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 | |
| bionlp-ost-19-BB-kb-ner-test | | | 125 | | ldeleger | 2023-11-28 | Developing | |
| bionlp-ost-19-SeeDev-bin-dev | | | 2.58 K | | ldeleger | 2023-11-28 | Developing | |
| LitCovid-PD-UBERON | | | 540 K | | Jin-Dong Kim | 2023-11-29 | | |
| Test_PubTator | | | 62 | | Chih-Hsuan Wei | 2023-11-29 | Testing | |
| 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 | |
| LitCovid-sample-docs | | A comprehensive literature resource on the subject of Covid-19 is collected by NCBI:
https://www.ncbi.nlm.nih.gov/research/coronavirus/
The LitCovid project@PubAnnotation is a collection of the titles and abstracts of the LitCovid dataset, for the people who want to perform text mining analysis. Please note that if you produce some annotation to the documents in this project, and contribute the annotation back to PubAnnotation, it will become publicly available together with contribution from other people.
If you want to contribute your annotation to PubAnnotation, please refer to the documentation page:
http://www.pubannotation.org/docs/submit-annotation/
The list of the PMID is sourced from here
Below is a notice from the original LitCovid dataset:
PUBLIC DOMAIN NOTICE
National Center for Biotechnology Information
This software/database is a "United States Government Work" under the
terms of the United States Copyright Act. It was written as part of
the author's official duties as a United States Government employee and
thus cannot be copyrighted. This software/database is freely available
to the public for use. The National Library of Medicine and the U.S.
Government have not placed any restriction on its use or reproduction.
Although all reasonable efforts have been taken to ensure the accuracy
and reliability of the software and data, the NLM and the U.S.
Government do not and cannot warrant the performance or results that
may be obtained by using this software or data. The NLM and the U.S.
Government disclaim all warranties, express or implied, including
warranties of performance, merchantability or fitness for any particular
purpose.
Please cite the authors in any work or product based on this material :
Chen Q, Allot A, & Lu Z. (2020) Keep up with the latest coronavirus research, Nature 579:193
| 0 | | Jin-Dong Kim | 2023-11-29 | Uploading | |
| acggdb_ggdb | | | 0 | | nfujita | 2023-11-29 | | |
| Training_Data_English_zh_en | | | 0 | | wmtbio | 2023-11-29 | Developing | |
| FirstAuthor_s_Plants | | For only Plants | 4.3 K | | AikoHIRAKI | 2023-11-29 | Testing | |
| bionlp-ost-19-BB-rel-dev | | | 1.97 K | | ldeleger | 2023-11-29 | Developing | |
| Training_Data_English_pt_en | | | 0 | | wmtbio | 2023-11-29 | Developing | |
| SNPPhenoExt | | | 3 | behrouz bokharaeian | bokharaeian | 2023-11-29 | Developing | |
| korean_corpus | | validation korean | 90 | | donghwan kim | 2023-11-29 | | |
