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NameTDescription# Ann.AuthorMaintainerUpdated_atStatus

41-60 / 264 show all
bionlp-st-ge-2016-test It is the benchmark test data set of the BioNLP-ST 2016 GE task. It includes Genia-style event annotations to 14 full paper articles which are about NFκB proteins. For testing purpose, however, annotations are all blinded, which means users cannot see the annotations in this project. Instead, annotations in any other project can be compared to the hidden annotations in this project, then the annotations in the project will be automatically evaluated based on the comparison. A participant of GE task can get the evaluation of his/her result of automatic annotation, through following process: Create a new project. Import documents from the project, bionlp-st-2016-test-proteins to your project. Import annotations from the project, bionlp-st-2016-test-proteins to your project. At this point, you may want to compare you project to this project, the benchmark data set. It will show that protein annotations in your project is 100% correct, but other annotations, e.g., events, are 0%. Produce event annotations, using your system, upon the protein annotations. Upload your event annotations to your project. Compare your project to this project, to get evaluation. GE 2016 benchmark data set is provided as multi-layer annotations which include: bionlp-st-ge-2016-reference: benchmark reference data set bionlp-st-ge-2016-test: benchmark test data set (this project) 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.7.99 KDBCLSJin-Dong Kim2020-09-18Released
bionlp-st-ge-2016-test-proteins Protein 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 KDBCLSJin-Dong Kim2020-09-18Released
craft-ca-core-ex-dev Development data for CRAFT CA shared task, core concepts + EXTENSIONS. This project contains the development (training) annotations for the Concept Annotation task of the CRAFT Shared Task 2019. This particular set of concept annotations is the "core+extensions" set. See the task description for details, but this set contains annotations to concepts that appear in the original 10 Open Biomedical Ontologies used for annotation PLUS annotations to extension classes created using the core concepts.90.2 KUniversity of Colorado Anschutz Medical Campuscraft-st2020-09-22Released
craft-ca-core-dev Development data for CRAFT CA shared task, core concepts only. This project contains the development (training) annotations for the Concept Annotation task of the CRAFT Shared Task 2019. This particular set of concept annotations is the "core" set. See the task description for details, but this set contains only annotations to concepts that appear in the original 10 Open Biomedical Ontologies used for annotation. (That is to say, it does not contain any annotations to extension classes).59.8 KUniversity of Colorado Anschutz Medical Campuscraft-st2020-09-22Released
Ab3P-abbreviations This corpus was developed during the creation of the Ab3P abbreviation definition identification tool. It includes 1250 manually annotated MEDLINE records. This gold standard includes 1221 abbreviation-definition pairs. Abbreviation definition identification based on automatic precision estimates Sunghwan Sohn, Donald C Comeau, Won Kim and W John Wilbur BMC Bioinformatics20089:402 DOI: 10.1186/1471-2105-9-4022.34 KSunghwan Sohn, Donald C Comeau, Won Kim and W John Wilburcomeau2016-07-29Beta
QFMC_MEDLINE Quaero French Medical Corpus: Annotation of MEDLINE titles5.97 KAurélie NévéolPierre Zweigenbaum2018-01-24Beta
Genomics_Informatics Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Text corpus for this journal annotated with various levels of linguistic information would be a valuable resource as the process of information extraction requires syntactic, semantic, and higher levels of natural language processing. In this study, we publish our new corpus called GNI Corpus version 1.0, extracted and annotated from full texts of Genomics & Informatics, with NLTK (Natural Language ToolKit)-based text mining script. The preliminary version of the corpus could be used as a training and testing set of a system that serves a variety of functions for future biomedical text mining.35.3 KHyun-Seok Parkewha-bio2018-11-27Beta
blah6_medical_device BLAH6 hackathon project to annotate medical device indications in premarket approval statement summaries. The documents in this project serve as a corpus of premarket approval (PMA) statements that have undergone quality control. In particular, we have (1) removed non-ascii characters, (2) fixed some text segmentation errors, and (3) fixed some capitalization errors.0Stefano Rensitherightstef2020-08-04Beta
FA_Top107-forWeb ※※※ !要データ加工! webリンク用には、この結果を加工して使っています。その他で使われる場合に、末尾記載の問題を別途解決する必要があります。 !要データ加工! ※※※ Top100+本来Top100に入るべきだった7レビューの計、107レビュー中99レビュー。 5414, 6076, 6930, 8403, 9643, 12112, 18544, 18829は、0denotationでドキュメント自体登録していません。 @AikoHIRAKIはtypoを修正したレビューフォルダ。 attributesの詳細はconfig参照。 ※※※ !注意! webリンク側のしばりで、選択文字列は複数のUniProtIDに対応していません。(例)Protein1~Protein7とある場合、 Protein1, 2, 3, 4, 5, 6, 7をさし、かつ全てにUniProtIDがあったとしても、1と7のみUniProtIDをとってきています。 "~"は、Protein2, 3, 4, 5, 6を意味していますが、positionではなく文字列で検索をかけているのと、見せ方の仕様上、これらのIDは全て未取得となっています。⇔GeneProteinでは"~"に2-6のIDsをもたせていました。 該当レビュー;14898(~=MAPK2, MAPK3, MAPK4, MAPK5, MAPK6), 10471(~=Ago2, Ago3) --------------------------------------- (例)ProteinAB...ProteinCD...ProteinB...ProteinDとある場合、 ProteinABは、ProteinAとBというLexical_Cueになっています。ProteinCDも同様に、ProteinCとD。BとDだけでは、このレビュー内ではProteinBやProteinDをさすことが分かるのですが、それ以外で使用する場合に、BとDにそれぞれ該当UniProtIDをあてるのは不適切です。 該当レビュー;11957(β4=itgb4, β1=itgb1, β5=itgb5, β3=itgb3) 他の例が出てきたら順次、ここに記載していきます。当座、これらは削除する必要があります。 attributeで削除フラグをつけるか、Jakeの機能がTextAEに実装されれば解決するか、検討して、何かしら分かるようにしておきます。 (例)ProteinA/B とある場合、 webリンクでは、"ProteinA"にUniProtID-Aを、"/B"にUniProtID-Bをつけています(リンク側のしばり)。webリンク以外で使われる場合には、別プロジェクトのFA_Top100Plus-GeneProteinで行っていたようなRelationを使って、"/B"ではなく、"ProteinB"として、UniProtID-Bと対応させる必要があります。現状のとり方ですと、要Relation箇所は救済出来ません。 Lexical cueには"/B"とありますが、Objectには"ProteinB"と残してあるので、Objectを参照して下さい。 但し、言語処理のようなpositionがご入用な場合には上では対応出来ていません。 該当レビュー;11935(/4=BMP4), 14898(/2=LATS2), 7412(/2=TSC2), 4629(/2=CtBP2) (webリンクでは、レビュー毎に完結しているので、"/B"がそのレビューで他の意味をなしていなければ対応出来るのと、文字列合致でリンクを貼っているためです。) !注意! ※※※ RelationのmergedはTextAEの既存機能で既に出来ます。10.3 KAikoHIRAKI2020-09-01Beta
Age_blah 1.45 Kslee72682020-09-17Beta
CoGe_Citation_Annotations Annotated PMC abstracts+full articles, that cite the "CoGe" papers (PMID: 18952863, 18269575). Total Num Citations: 165 Total Num Unique Citations: 141 Total Num Abstracts: 165 Total Num Whole Articles: 165 0Heather Lenthclent2016-10-11Uploading
OryzaGP1 A dataset for Named Entity Recognition for rice gene0Huy Do. Pierre Larmande2019-01-31Uploading
FA_Top100Plus-GeneProtein Top100+本来Top100に入るべきだった7レビューの計、107レビュー中101レビュー。 5414, 6076, 6930, 8403, 9643, 18544は、0denotationでドキュメント自体登録していない。 attributesの詳細はconfig参照。 ドキュメントのソースDBが@AikoHIRAKIとなっているものはTypo修正がPubAnnotationの公式FirstAuthorsドキュメントに反映された段階で置き換えます。 10.4 Kyucca2020-09-14Uploading
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.687NaCTeMYue Wang2020-09-17Uploading
tagtog OpenAccess annotations coming from tagtog.net0tagtogtagtog2015-02-23Developing
KAIST_NLP_Annotation3 4.73 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation4 5.18 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation5 6.27 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation6 4.47 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation7 4.64 Kkaist_nlp2015-09-21Developing
NameT# Ann.AuthorMaintainerUpdated_atStatus

41-60 / 264 show all
bionlp-st-ge-2016-test 7.99 KDBCLSJin-Dong Kim2020-09-18Released
bionlp-st-ge-2016-test-proteins 4.34 KDBCLSJin-Dong Kim2020-09-18Released
craft-ca-core-ex-dev 90.2 KUniversity of Colorado Anschutz Medical Campuscraft-st2020-09-22Released
craft-ca-core-dev 59.8 KUniversity of Colorado Anschutz Medical Campuscraft-st2020-09-22Released
Ab3P-abbreviations 2.34 KSunghwan Sohn, Donald C Comeau, Won Kim and W John Wilburcomeau2016-07-29Beta
QFMC_MEDLINE 5.97 KAurélie NévéolPierre Zweigenbaum2018-01-24Beta
Genomics_Informatics 35.3 KHyun-Seok Parkewha-bio2018-11-27Beta
blah6_medical_device 0Stefano Rensitherightstef2020-08-04Beta
FA_Top107-forWeb 10.3 KAikoHIRAKI2020-09-01Beta
Age_blah 1.45 Kslee72682020-09-17Beta
CoGe_Citation_Annotations 0Heather Lenthclent2016-10-11Uploading
OryzaGP1 0Huy Do. Pierre Larmande2019-01-31Uploading
FA_Top100Plus-GeneProtein 10.4 Kyucca2020-09-14Uploading
AnEM_full-texts 687NaCTeMYue Wang2020-09-17Uploading
tagtog 0tagtogtagtog2015-02-23Developing
KAIST_NLP_Annotation3 4.73 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation4 5.18 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation5 6.27 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation6 4.47 Kkaist_nlp2015-09-21Developing
KAIST_NLP_Annotation7 4.64 Kkaist_nlp2015-09-21Developing