Difference between revisions of "Corpus Create Annotation Schema By Abner"
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'''NLPBA''' (model trained with the NLPBA corpus). | '''NLPBA''' (model trained with the NLPBA corpus). | ||
| − | Pressing'''Ok''' the operation will be launched and a progress window will n+be shown, indicating the execution of the operation and estimate time left. | + | Pressing '''Ok''' the operation will be launched and a progress window will n+be shown, indicating the execution of the operation and estimate time left. |
The NER operation will take a few minutes or hours depending on the number of documents, document size and used resources. | The NER operation will take a few minutes or hours depending on the number of documents, document size and used resources. | ||
When the process terminates, a new '''NER Process''' object will be added to the [[Corpora_Load_Corpus|''Corpus Process View'']]. | When the process terminates, a new '''NER Process''' object will be added to the [[Corpora_Load_Corpus|''Corpus Process View'']]. | ||
Revision as of 00:25, 16 January 2013
The user can perform an NER process using the Abner algorithm (for more details please visit http://gate.ac.uk/sale/tao/splitch16.html#sec:parsers:abner ).
Selecting the Corpus object on the clipboard, you should right click over it an choose Corpus -> NER -> Abner Tagging
A GUI will be presented, where you can select the training model to be used with ABNER, from the options:
BIOCREATIVE (model trained with the BioCreative corpus).
NLPBA (model trained with the NLPBA corpus).
Pressing Ok the operation will be launched and a progress window will n+be shown, indicating the execution of the operation and estimate time left. The NER operation will take a few minutes or hours depending on the number of documents, document size and used resources.
When the process terminates, a new NER Process object will be added to the Corpus Process View.
