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Jin-Dong Kim
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Collections
NameDescriptionUpdated at
1-10 / 12 show all
GlycoBiologyAnnotations made to the titles and abstracts of the journal 'GlycoBiology'2019-03-10
PreeclampsiaPreeclampsia-related annotations for text mining2019-03-10
bionlp-st-ge-2016The 2016 edition of the Genia event extraction (GE) task organized within BioNLP-ST 20162019-03-11
GlyCosmos600A random collection of 600 PubMed abstracts from 6 glycobiology-related journals: Glycobiology, Glycoconjugate journal, The Journal of biological chemistry, Journal of proteome research, Journal of proteomics, and Carbohydrate research. The whole PMIDs were collected on June 11, 2019. From each journal, 100 PMIDs were randomly sampled.2021-10-22
LitCovid-v1This collection includes the result from the Covid-19 Virtual Hackathon. LitCovid is a comprehensive literature resource on the subject of Covid-19 collected by NCBI: https://www.ncbi.nlm.nih.gov/research/coronavirus/ Since the literature dataset was released, several groups are producing annotations to the dataset. To facilitate a venue for aggregating the valuable resources which are highly relevant to each other, and should be much more useful when they can be accessed together, this PubAnnotation collection is set up. It is a part of the Covid19-PubAnnotation project. In this collection, the LitCovid-docs project contains all the documents contained in the LitCovid literature collection, and the other projects are annotation datasets contributed by various groups. It is an open collection, which means anyone who wants to contribute can do so, in the following way: take the documents in the, LitCovid-docs project produce annotation to the texts based on your resource, and contribute the annotation back to this collection: create your own project at PubAnnotaiton, upload your annotation to the project (HowTo), and add the project to this collection. All the contributed annotations will become publicly available. Please note that, during uploading your annotation data, you do not need to be worried about slight changes in the text: PubAnnotation will automatically catch them and adjust the positions appropriately. Should you have any question, please feel free to mail to admin@pubannotation.org. 2020-11-20
LitCovid-sampleVarious annotations to a sample set of LitCovid, to demonstrate potential of harmonized various annotations.2021-01-14
CORD-19-sample-annotation2020-04-21
LitCovid2021-10-18
LitCoin2021-12-14
LitCoin-Test2021-12-23
Projects
NameTDescription# Ann.Updated atStatus
141-150 / 159 show all
test102122023-11-24
PubMed-German-testA collection of PubMed abstracts which are written in German02023-11-24Developing
PubMed-2017abstracts published in 2017.02023-11-24Developing
speech-test62023-11-26Testing
CORD-19-SciBite-sentences11.2 K2023-11-26Testing
LitCovid-PD-FMA-UBERON-v1PubDictionaries annotation for anatomy terms - updated at 2020-04-20 Disease term annotation based on FMA and Uberon. Version 2020-04-20. The terms in FMA and Uberon are loaded in PubDictionaries (FMA and Uberon), with which the annotations in this project are produced. The parameter configuration used for this project is here for FMA and there for Uberon. Note that it is an automatically generated dictionary-based annotation. It will be updated periodically, as the documents are increased, and the dictionary is improved.4.3 K2023-11-27Released
bionlp-st-ge-2016-test-proteinsProtein 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 K2023-11-27Released
GlyCosmos600-GlycoProteinsGlycoProtein annotations were made using the glycoprotein-name dictionary on PubDictionaries: http://pubannotation.org/projects/GlyCosmos600-docs The documents were imported from the GlyCosmos600-docs project: http://pubannotation.org/projects/GlyCosmos600-docs3.68 K2023-11-27Testing
bionlp-st-ge-2016-corefCoreference annotation to the benchmark data set (reference and test) of BioNLP-ST 2016 GE task. For detailed information, please refer to the benchmark reference data set (bionlp-st-ge-2016-reference) and benchmark test data set (bionlp-st-ge-2016-test).8532023-11-28Released
pubmed-sentences-benchmarkA 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 K2023-11-28Released
Automatic annotators
Editors
NameDescription
1-2 / 2
TextAE-oldTextAE version 4, which was the latest stable version until Apr. 19, 2020.
TextAETextAE version 5, which enables edition of attributes of denotations.