Auto-suggest related resources through named entity recognition (NER)

[Driebot]

In gitlab by david on Mar 21, 2016, 17:23

In admin, parse resource body text and recognise keywords in Ginger. Then based on those resources, automatically suggest related resources. Content editors can then accept/reject the suggestions. When they accept, create an outgoing edge to the selected resource(s).

For parsing the text:

• Apache Stanbol
• DBpedia Spotlight can also be used with other datasets, your own text, in custom domains, etc. This will require that you rebuild the models using our Data Generation https://github.com/dbpedia-spotlight/dbpedia-spotlight/wiki/Data-generation-manual pipeline.

Also needs some UI work where editors can accept/reject suggestions.

/cc @emine @fred

[ddeboer]

Can https://research.googleblog.com/2016/05/announcing-syntaxnet-worlds-most.html help? Seems to be about language understanding (syntax/grammar) rather than simply extracting entities.

[Dirklectisch]

You are certainly right that it is more advanced than just ripping out the entities. But it can also just filter nouns, verbs or whatever you want (if I understand that blog post correctly).

[fredpook]

DBpedia spotlight already filters "noise" since the entities come from crowd-sourced wikipedia pages.

[ddeboer]

We now have a DBpedia Spotlight module for extracting DBpedia resources from text.