resources:existing

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-====== List of existing resources useful for natural language processing for pharmacovigilance ====== +====== List of existing resources useful for natural language processing in the pharmacovigilance domain ====== 
-  * source: type of source, e.g., scientific paper, abstract, drug leaflet, patient forum, tweet, etc. +  * **source**: type of source, e.g., scientific paper, abstract, drug leaflet, patient forum, tweet, etc. 
-  * lang = languages: comma-separated list of 2-letter ISO codes +  * **lang** = languages: comma-separated list of 2-letter ISO codes 
-  * description: short characterization of the corpus +  * **description**: short characterization of the corpus 
-  * noteworthiness: any specific feature of this dataset +  * **noteworthiness**: any specific feature of this dataset 
-  * NER: are entities annotated, and for what types of entities +  * **NER**: are entities annotated, and for what types of entities 
-  * linking: is entity linking provided, and to what ontologies +  * **linking**: is entity linking provided, and to what ontologies 
-  * REL: are relations annotated+  * **REL**: are relations annotated
     * IE = information extraction style: between entity instances (one per pair of entity spans),     * IE = information extraction style: between entity instances (one per pair of entity spans),
     * KB = knowledge-base style: between entities (one per text and pair of [linked] entities),     * KB = knowledge-base style: between entities (one per text and pair of [linked] entities),
     * CL = text classification style: presence of a relation between entity types (one per text and pair of entity types); if only one type of relation is considered, this is a binary text classification task     * CL = text classification style: presence of a relation between entity types (one per text and pair of entity types); if only one type of relation is considered, this is a binary text classification task
-  * REL list: if REL is non null, list of annotated relations +  * **REL list**: if REL is non null, list of annotated relations 
-  * format: CONLL, BRAT, etc. +  * **format**: CONLL, BRAT, etc. 
-  * size: number of language units such as documents, sentences, words (please no megabytes) +  * **size**: number of language units such as documents, sentences, words (please no megabytes) 
-  * publication: reference to a publication (peer-reviewed rather than preprint) +  * **publication**: reference to a publication (peer-reviewed rather than preprint) 
-  * URL: URL where the dataset can be downloaded or is described+  * **URL**: URL where the dataset can be downloaded or is described
  
  
 ^ name ^ source ^ lang ^ description ^ noteworthiness ^ NER ^ linking ^ REL ^ REL list ^ format ^ size ^ publication ^ URL ^ ^ name ^ source ^ lang ^ description ^ noteworthiness ^ NER ^ linking ^ REL ^ REL list ^ format ^ size ^ publication ^ URL ^
-^ TLC | patient forum | de | annotated dataset with laymen expressions | | laymen terms, including their technical term; technical term with a rather laymen term | no | no | | | BRAT | 4000 documents | https://www.aclweb.org/anthology/2020.lrec-1.759/ | http://macss.dfki.de/data/LREC2020/TLC_v01.tar.gz |+^ TLC | patient forum | de | dataset annotated with layman expressions: Fachterm, Laienbegriff, Abkürzung | | layman terms, including their associated technical terms; technical term with a rather layman term | no | no | | | BRAT | 4000 documents | https://www.aclweb.org/anthology/2020.lrec-1.759/ | http://macss.dfki.de/data/LREC2020/TLC_v01.tar.gz |
  
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  • Last modified: 2021/05/12 17:02
  • by pz