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Posted to commits@stanbol.apache.org by "Rafa Haro (JIRA)" <ji...@apache.org> on 2013/09/11 18:45:52 UTC
[jira] [Updated] (STANBOL-1157) Freebase Disambiguation Algorithm
[ https://issues.apache.org/jira/browse/STANBOL-1157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Rafa Haro updated STANBOL-1157:
-------------------------------
Description:
The disambiguation algorithm should take into account a local disambiguation score (comparing in some way the document context with the contexts provided by Wikilinks resource) and a global disambiguation score computed by a graph based algorithm using the Freebase graph imported in a Neo4j database. Each disambiguation score would have a different weight in the final disambiguation store for each entity. The algorithm's steps, for each TextAnnotation, can be the following:
1. Local score: for each EntityAnnotation, retrieves from Wikilinks database all the contexts associated to the referenced entity. Compare (similarity, distance....) the mention context (selected-context) with the wikilinks contexts.
2. Global score: build a subgraph with all the possible entities and its relations in Freebase. Extract a set of possibles solutions from such graph (note: a solution should include only one entity annotation for each text annotation). Compute the Dijsktra distance between each pair of entities belonging to a possible solution.
3. Weights normalization and confidence values refinement.
> Freebase Disambiguation Algorithm
> ---------------------------------
>
> Key: STANBOL-1157
> URL: https://issues.apache.org/jira/browse/STANBOL-1157
> Project: Stanbol
> Issue Type: Sub-task
> Components: Enhancement Engines, Enhancer, Entityhub
> Reporter: Rafa Haro
> Fix For: 0.12.0
>
> Original Estimate: 672h
> Remaining Estimate: 672h
>
> The disambiguation algorithm should take into account a local disambiguation score (comparing in some way the document context with the contexts provided by Wikilinks resource) and a global disambiguation score computed by a graph based algorithm using the Freebase graph imported in a Neo4j database. Each disambiguation score would have a different weight in the final disambiguation store for each entity. The algorithm's steps, for each TextAnnotation, can be the following:
> 1. Local score: for each EntityAnnotation, retrieves from Wikilinks database all the contexts associated to the referenced entity. Compare (similarity, distance....) the mention context (selected-context) with the wikilinks contexts.
> 2. Global score: build a subgraph with all the possible entities and its relations in Freebase. Extract a set of possibles solutions from such graph (note: a solution should include only one entity annotation for each text annotation). Compute the Dijsktra distance between each pair of entities belonging to a possible solution.
> 3. Weights normalization and confidence values refinement.
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