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Jin-Dong Kim
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Name DescriptionUpdated at
11-12 / 12 show all
CORD-19CORD-19 (COVID-19 Open Research Dataset) is a free, open resource for the global research community provided by the Allen Institute for AI: https://pages.semanticscholar.org/coronavirus-research. As of 2020-03-20, it contains over 29,000 full text articles. This CORD-19 collection at PubAnnotation is prepared for the purpose of collecting annotations to the texts, so that they can be easily accessed and utilized. If you want to contribute with your annotation, take the documents in the CORD-19_All_docs project, produce your annotation to the texts using your annotation system, and contribute the annotation back to PubAnnotation (HowTo). 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. Once you have uploaded your annotation, please notify it to admin@pubannotation.org admin@pubannotation.org, so that it can be included in this collection, which will make your annotation much easily findable. Note that as the CORD-19 dataset grows, the documents in this collection also will be updated. IMPORTANT: CORD-19 License agreement requires that the dataset must be used for text and data mining only.2020-04-14
bionlp-st-ge-2016The 2016 edition of the Genia event extraction (GE) task organized within BioNLP-ST 20162019-03-11
Projects
NameTDescription# Ann.Updated atStatus
121-130 / 163 show all
GO-BPAnnotation for biological processes as defined in the "Biological Process" subset of Gene Ontology35.4 K2023-11-29Developing
GO-MFAnnotation for molecular functions as defined in the "Molecular Function" subtree of Gene Ontology19.7 K2023-12-04Testing
bionlp-st-ge-2016-referenceIt is the benchmark reference data set of the BioNLP-ST 2016 GE task. It includes Genia-style event annotations to 20 full paper articles which are about NFκB proteins. The task is to develop an automatic annotation system which can produce annotation similar to the annotation in this data set as much as possible. For evaluation of the performance of a participating system, the system needs to produce annotations to the documents in the benchmark test data set (bionlp-st-ge-2016-test). GE 2016 benchmark data set is provided as multi-layer annotations which include: bionlp-st-ge-2016-reference: benchmark reference data set (this project) bionlp-st-ge-2016-test: benchmark test data set (annotations are blined) bionlp-st-ge-2016-test-proteins: protein annotation to the benchmark test data set Following is supporting resources: bionlp-st-ge-2016-coref: coreference annotation bionlp-st-ge-2016-uniprot: Protein annotation with UniProt IDs. pmc-enju-pas: dependency parsing result produced by Enju UBERON-AE: annotation for anatomical entities as defined in UBERON ICD10: annotation for disease names as defined in ICD10 GO-BP: annotation for biological process names as defined in GO GO-CC: annotation for cellular component names as defined in GO A SPARQL-driven search interface is provided at http://bionlp.dbcls.jp/sparql.14.4 K2023-11-29Released
Glycosmos6-MATAutomatic annotation by PD-MAT.263 K2023-11-29Developing
GlycosmosP-GlycoEpitope242023-11-29Testing
sentencesSentence segmentation annotation. Automatic annotation by TextSentencer.6.96 M2023-11-24Developing
Test-Documents12023-11-24
GlyCosmosP-Glycan-Motif82023-11-24Developing
MENA-example232023-11-24Testing
Glycosmos6-GlycoEpitopeAutomatic annotation by PD-GlycoEpitope.19.9 K2023-11-28Developing
Automatic annotators
NameDescription
1-10 / 38 show all
PubTator-ChemicalTo pull the pre-computed chemical annotation from PubTator.
PubTator-GeneTo pull the pre-computed gene annotation from PubTator.
PubTator-SpeciesTo pull the pre-computed Species annotation from PubTator.
PubTator-DiseaseTo pull the pre-computed disease annotation from PubTator.
PubTator-MutationTo pull the pre-computed mutation annotation from PubTator.
discourse-simplifierA discourse analyzer developed by Univ. Manchester.
PD-NGLY1-deficiency-BA batch annotator for NGLY1 deficiency
PD-UBERON-AEIt annotates for anatomical entities, based on the UBERON-AE dictionary on PubDictionaries. Threshold is set to 0.85.
PD-MONDOPubDictionaries annotation with the MONDO dictionary.
PD-FMA-PAEPhysical Anatomical Entities from FMA
Editors
NameDescription
1-1 / 1
TextAEThe official stable version of TextAE.