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filter endpoint #93
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I like the first solution you've proposed. But we need to talk about this one too. |
@jnehring I am afraid I don't get it. Is your solution proposing that we first receive the NIF based return and then send that return back to a filter which then returns the delta that we need? |
No. The proposed solution is that you send your content to FREME and then 2015-11-25 17:10 GMT+01:00 Kevin Koidl notifications@github.com:
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P.S.: you could send things twice, but that is not needed. 2015-11-25 17:16 GMT+01:00 Felix Sasaki felix.sasaki@googlemail.com:
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I have two ideas how the workflow of using this could look like. Here an example for the WRIPL use case of e-Terminology: First idea: With pipelines
2nd idea: With extra parameter Step 1) and 2) same as above Actually I think that the 2nd approach is easier for the users. There is a little more implementation work but it saves us the work of creating the pipelines. |
Sounds good. 2015-11-26 10:01 GMT+01:00 Jan Nehring notifications@github.com:
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@jnehring that sounds great! Some minor questions/comments
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+1 to 2) from Kevin. Also, I see that people want to have simple output Best, Felix 2015-11-26 11:39 GMT+01:00 Kevin Koidl notifications@github.com:
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That result looks clean. @Xfran what do you think? In relation to the queries we 'simply' need the entity label, the entity reference (URL) and the Entity Type to start with. The Entity Type is an interesting one to us because it allows us to filter out for example "Type:Thing". I am not sure however how to deal with the datasets in future. The Entity Type relates to the dbpedia dataset. Things that might trigger questions (or which we should discuss now) are:
Is this helpful. Or will I try to construct a query example...? Kevin |
That's helpful, thanks. I'll create a query example by next week or before. |
Thanks @fsasaki looking forward to it |
It should be possible to create a pipeline that calls 1) e-eEntity, 2) calls e-Terminology and 3) applies the filter. A dedicated filter needs to be created for this.
I agree. The output of the filter is RDF so it can be JSON-LD. |
The output of a sparql query would be RDF result format which can be stored as json or in a different syntax, but it won't be jsonl-ld. |
Implemented. See documentation in http://api-dev.freme-project.eu/doc/knowledge-base/filtering.html |
We could implement an endpoint
/toolbox/filter/{filter-id}
. Each filter is a SPARQL query. When you submit RDF data to the filter, then the SPARQL query is executed on the RDF and the result is returned to the user. So the general idea is to filter out some triples out of NIF.This can have two applications
a) Make the output of an e-Service easier. When someone says "I dont want to see NIF, I just want to get all entities in a text" then we can create a filter that extracts the entities from NIF. Then the user can create a pipeline that calls e-Entity first to extract entities. Then it calls the filter to drop all other information in the NIF response apart from the entities.
b) Long pipelines might suffer from the problem that they produce more and more NIF and therefore they process a lot of data. Also some unnecessary data processing might occur. Using the filter you can filter out some data inside of the pipeline.
This might be a feature of FREME 0.5. It might make #89 obsolete.
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