The number of pipelines is configured in the file *confignerc.properties*. The option format is:
{code:java}
com.ontotext.kim.semanticannotation.PARALLEL_NERCS=<maximum number of parallel executions allowed>
{code}Examples:
{code:java}
com.ontotext.kim.semanticannotation.PARALLEL_NERCS=1
#will disable parallel annotation
com.ontotext.kim.semanticannotation.PARALLEL_NERCS=auto
#will limit the number of parallel executions to the number of CPU cores, available in the system
com.ontotext.kim.semanticannotation.PARALLEL_NERCS=3
#will process up to 3 annotation executions at the same time
{code}
h2. Extending the information extraction
After you have extended the ontology with domain specific classes and have enriched the knowledge base with instances, there are three options for configuring the IE process:
* You can use both the default IE module and the grammars. If you have followed the above steps correctly, you can rely on the module and grammars to recognize entities correctly.
* You can leave the default IE module as it is, but edit some of the grammars to provide specific recognition rules. (We do not recommended it.)
* You can create a new IE module {{*.gapp}} and develop grammars to cover the desired domain. Replace the default IE module with the new IE module. (This is a complex task and we recommend it to advanced GATE users only. It is not discussed here.)
(!) The first IE module on the list is used by default.
{tip:title=Tips}
Increasing the number of allowed parallel executions will increase the memory requirements of the server. Therefore, we do not recommend to set this number above the number of CPU cores in the system. Doing so will only waste memory. If you allow parallel annotation, make sure you [increase the allotted memory to the server|Configuring remote connection].
* Parallel annotation leads to loading multiple documents in KIM simultaneously. Documents with more than 20 pages will take up to 1 GB of memory. If you intend to annotate large documents in parallel, keep in mind that the KIM server will require a lot of memory.
{noformat}<required memory> =
<memory in minimal requirements> +
<number of parallel executions allowed> * <memory required for processing 1 document>{noformat}
* Even though the regular [Populater Tool|Population] does not take advantage of parallel annotation, you can start several separate Populater instances on different subsets of documents at the same time. Due to the fact that these different instances will work in parallel, this approach will take less time, compared to running a single Populater Tool instance for all documents.{tip}