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AGACThis is the collection for AGAC track data, a subtask in BioNLP OST 2019, Hong Kong. xiajingbo2019-03-13
DPCIRCTSuexuan2024-08-20
NeuroBridge Testraywang2021-05-13
190926nakazato2019-09-26
RDoCTaskmmanani1s2019-03-16
bionlp-ost-19-BB-kb-nerBB-kb+ner subtask of the Bacteria Biotope task proposed at BioNLP-OST 2019. BB-kb+ner is an entity recognition, normalization and relation extraction task. Homepage of Bacteria Biotope: https://sites.google.com/view/bb-2019/homeldeleger2020-02-07
bionlp-ost-19-SeeDev-binarySeeDev-binary subtask of the SeeDev task proposed at BioNLP-OST 2019. SeeDev-binary is a binary relation extraction task. Homepage of SeeDev: https://sites.google.com/view/seedev2019/homeldeleger2020-02-07
bionlp-ost-19-BB-rel-nerBB-rel+ner subtask of the Bacteria Biotope task proposed at BioNLP-OST 2019. BB-rel+ner is an entity recognition and relation extraction task. Homepage of Bacteria Biotope: https://sites.google.com/view/bb-2019/homeldeleger2020-02-07
bionlp-ost-19-BB-normBB-norm subtask of the Bacteria Biotope task proposed at BioNLP-OST 2019. BB-norm is an entity normalization task.ldeleger2020-02-07
bionlp-ost-19-BB-norm-nerBB-norm+ner subtask of the Bacteria Biotope task proposed at BioNLP-OST 2019. BB-norm+ner is an entity recognition and normalization task.ldeleger2020-02-07
bionlp-ost-19-BB-relBB-rel subtask of the Bacteria Biotope task proposed at BioNLP-OST 2019. BB-rel is a relation extraction task. Homepage of Bacteria Biotope: https://sites.google.com/view/bb-2019/home ldeleger2020-02-07
bionlp-ost-19-BB-kbBB-kb subtask of the Bacteria Biotope task proposed at BioNLP-OST 2019. BB-kb is an entity normalization and relation extraction task. Homepage of Bacteria Biotope: https://sites.google.com/view/bb-2019/homeldeleger2020-02-07
bionlp-st-ge-2016The 2016 edition of the Genia event extraction (GE) task organized within BioNLP-ST 2016Jin-Dong Kim2019-03-11
LASIGE: Annotating a multilingual COVID-19-related corpus for BLAH7The global motivation is the creation of parallel multilingual datasets for text mining systems in COVID-19-related literature. Tracking the most recent advances in the COVID-19-related research is essential given the novelty of the disease and its impact on society. Still, the pace of publication requires automatic approaches to access and organize the knowledge that keeps being produced every day. It is necessary to develop text mining pipelines to assist in that task, which is only possible with evaluation datasets. However, there is a lack of COVID-19-related datasets, even more, if considering other languages besides English. The expected contribution of the project will be the annotation of a multilingual parallel dataset (EN-PT), providing this resource to the community to improve the text mining research on COVID-19-related literature.dpavot2021-02-17