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Posted to commits@stanbol.apache.org by "Rupert Westenthaler (JIRA)" <ji...@apache.org> on 2013/10/03 08:40:42 UTC

[jira] [Resolved] (STANBOL-1128) Implement a Lucene FST based Entity Linking Engine (based on OpenSextant / SolrTextTagger)

     [ https://issues.apache.org/jira/browse/STANBOL-1128?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Rupert Westenthaler resolved STANBOL-1128.
------------------------------------------

    Resolution: Fixed

resolved with http://svn.apache.org/r1528716

The engine is included in the default build. Its available in both the stable and the full launcher. A default configuration for FST linking against the default dbpedia dataset was also added (chain name: dbpedia-fst-linking)

For more information and some performance statistics see http://stanbol.markmail.org/thread/d7o5k44xbh4jwfjh



> Implement a Lucene FST based Entity Linking Engine (based on OpenSextant / SolrTextTagger)
> ------------------------------------------------------------------------------------------
>
>                 Key: STANBOL-1128
>                 URL: https://issues.apache.org/jira/browse/STANBOL-1128
>             Project: Stanbol
>          Issue Type: New Feature
>          Components: Enhancement Engines
>            Reporter: Rupert Westenthaler
>            Assignee: Rupert Westenthaler
>
> This will implement an in-memory EntityLinking EnhancementEngine based on Lucenes FST (Finite State Transducer) technology.
> This engine could make direct use of the Classes contained in the OpenSextant / SolrTextTagger code [1]. This uses a two layered FST 
>     (1) to represent words and 
>     (2) to map those words to phrases
> With this it is possible to efficiently hold big vocabularies in memory (> 300MByte for geonames.org). See the presentation at [2] for more details.
> While the license is fully compatible (ASL 2.0) the library is currently not available on Maven Central. We need to contact the author regarding this.
> [1] https://github.com/OpenSextant/SolrTextTagger
> [2] http://www.lucenerevolution.org/2013/Text-Tagging-with-Finite-State-Transducers



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