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From "Tommaso Teofili (JIRA)" <>
Subject [jira] Commented: (SOLR-2129) Provide a Solr module for dynamic metadata extraction/indexing with Apache UIMA
Date Tue, 05 Oct 2010 15:58:32 GMT


Tommaso Teofili commented on SOLR-2129:

Robert thanks for that, I confirm that UIMA doesn't require java 6, java 5 is fine so this
is fine for branc_3x too.

Jörn, good to see you here too :) you can run also custom UIMA Analysis.
By default the default AEs are WhitespaceTokenizer, Tagger, AlchemyAPIAnnotator, OpenCalaisAnnotator.

To customize the default behavior you should:
a) change the OverridingParamsExtServicesAEDescriptor and (eventually) eventually extend BaseUIMAUpdateRequestProcessor
and its SolrUIMAConsumers


b) define a new AE descriptor and create for it a new class extending UIMAUpdateRequestProcessor
(or extend BaseUIMAUpdateRequestProcessor) then modify the UIMAUpdateRequestProcessorFactory
to initialize that class instead of the base one.

If you need any parameters to be set at runtime for a delegate AE, you must set, inside the
aggregate AE, an overriding parameter that overrides some parameter in the delegate AE and
then define its runtime value in solrconfig with:


> Provide a Solr module for dynamic metadata extraction/indexing with Apache UIMA
> -------------------------------------------------------------------------------
>                 Key: SOLR-2129
>                 URL:
>             Project: Solr
>          Issue Type: New Feature
>            Reporter: Tommaso Teofili
>            Assignee: Robert Muir
>         Attachments:, SOLR-2129-asf-headers.patch, SOLR-2129.patch
> Provide components to enable Apache UIMA automatic metadata extraction to be exploited
when indexing documents.
> The purpose of this is to get unstructured information "inside" a document and create
structured metadata (as fields) to enrich each document.
> Basically this can be done with a custom UpdateRequestProcessor which triggers UIMA while
indexing documents.
> The basic UIMA implementation of UpdateRequestProcessor extracts sentences (with a tokenizer
and an hidden Markov model tagger), named entities, language, suggested category, keywords
and concepts (exploiting external services from OpenCalais and AlchemyAPI). Such an implementation
can be easily extended adding or selecting different UIMA analysis engines, both from UIMA
repositories on the web or creating new ones from scratch.

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