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https://issues.apache.org/jira/browse/STANBOL-1157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Rafa Haro updated STANBOL-1157:
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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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