Hi Pajolma, As far as I know there are no separate evaluations out of the box, but you could use the milne-witten corpus to evaluate only the spottter and disambiguation separately.
In my experience problems are usually related to spotting: surface forms which are not in the models, surface forms without enough probability. There is also specific corpus for evaluating disambiguation (kore50) On Tue, Jun 2, 2015 at 1:58 PM, Pajolma Rupi <[email protected]> wrote: > Dear all, > > I was not able to find some information regarding the time performance of > Spotlight service for each of the phases (separately): phrase spotting > (candidate generation, candidate selection), disambiguation, indexing.There > are some numbers present in the paper "*Improving efficiency and accuracy > in multilingual entity extraction*" but they are calculated in the > context of all the annotation process, meanwhile I'm interested in knowing > during which specific phase the service performs better and during which > phase it performs worse. > > Could you please let me know if such information exists already? > I would also be interested in knowing if I can produce such information by > running my own local instance of Spotlight (I'm using Java in order to > annotate text). > > Thank you in advance, > Pajolma > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Dbp-spotlight-users mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/dbp-spotlight-users > >
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