Hi Stefano,
Yes, In the calculations I refer to the second candidate.
I'm a bit confused, what do you mean with "confidence"?
There is a spotlight branch, we have been working on with Relevance Scores.
The Relevance Score is related to the importance of an entity in the text,
I wonder if this is somehow interesting for what you are doing.
David
On Fri, Jun 20, 2014 at 3:18 PM, Stefano Bocconi <[email protected]>
wrote:
> Hi Radim,
>
> I have not evaluated my formula, I thought it was a more or less logical
> combination of how sure Spotlight was of the first candidate and whether
> the second candidate was also at the same level.
>
> In David’s explanation I think that the second rank is not calculated
> with the bottom entity, but with the second best. So if I am very sure of
> the first candidate, but also of the second, I get a 50% change that either
> is true.
>
> Now it turns out that this is not “confidence”, but “disambiguation”, so
> Spotlight could be very sure to have disambiguated the wrong entity, but it
> seems there is not concept of confidence at the moment in Spotlight.
>
> As I wrote in another mail, the candidates REST function has some more
> info for each candidate, so there are more parameters to study,
> unfortunately I doubt I will have the time to do so now.
>
> In any case I have to manually evaluate something like 500 tweets, I
> might reuse this corpus in the future to correlate it to the other
> parameters.
>
> Regards,
>
> Stefano
>
> From: Radim Rehurek <[email protected]>
> Date: Tuesday 17 June 2014 11:37
> To: David Przybilla <[email protected]>
> Cc: Stefano Bocconi <[email protected]>, "
> [email protected]" <
> [email protected]>
> Subject: Re: [Dbp-spotlight-users] How is the confidence value calculated?
>
> Thanks David.
>
> If I understand your reply correctly, you're advocating using
> "similarityScore" directly as Spotlight's detection confidence.
>
> I wonder if this is better than Stefano's formula. Stefano, did you
> evaluate your formula somehow? Mixing support into the confidence formula
> makes good sense to me too.
>
> Best,
> Radim
>
>
>
>
>
> ---------- Původní zpráva ----------
> Od: David Przybilla <[email protected]>
> Komu: Radim Rehurek <[email protected]>
> Datum: 17. 6. 2014 11:06:01
> Předmět: Re: [Dbp-spotlight-users] How is the confidence value calculated?
>
> Hi Radim, Stefano,
>
> 1. This is roughly how I think it works, best to confirm checking some
> code/paper:
>
> So the support you give via the endpoint serve as a filter over how many
> annotated counts an entity should have.
>
> The confidence value you give via the endpoint is used twice:
>
> - To filter spots ( chunks of surfaceforms which will be matched later to
> a topic)
> - To Filter topic annotations (once you have disambiguated) ( secondRank
> Filter is also used in this stage)
>
>
> Similarity_of_t = ln(surfaceForm Prior ) + ln(prior_of_t) +
> contextSimilarity_for_t
> softTotalSimilarity = sum(e ^ Similarity_of_i)
> final_similarity_of_t = e ^(Similarity_of_t - softTotalSimilarity)
>
>
> -- order the topics by similarity(greaterFirst
> secondRank = e ^(bottomTopicFinalSimilarityScore -
> topTopicFinalSimilarityScore)
>
> topics with : secondRank > (1 - confidence ^2) are filtered
>
>
> 2. what is the best value ?
>
> I think this really depends on your use-case, for example if you need
> lots of general topics you might want to have a low value, however be
> prepared for a wave of dodgy topics and surface forms annotations as well.
>
> If you are doing social-media most likely you have lots of surface forms
> and variations of them which are not getting spotted because of the
> confidence value.
> My advice is to empirically adjust the confidence and support value and
> then tweak the spotlight model to adapt it to your particular use case [1]
>
> [1] https://github.com/idio/spotlight-model-editor
>
>
>
> On Mon, Jun 16, 2014 at 5:32 PM, Radim Rehurek <[email protected]>
> wrote:
>
> I would be also extremely interested in an answer to this. Thanks for
> asking, Stefano.
>
> What's the best way to calculate "Spotlight's detection confidence" = a
> single number?
>
> Cheers,
> Radim
>
> ---------- Původní zpráva ----------
> Od: Stefano Bocconi <[email protected]>
> Komu: [email protected] <
> [email protected]>
> Datum: 16. 6. 2014 18:14:26
> Předmět: [Dbp-spotlight-users] How is the confidence value calculated?
>
> Hi,
>
> I am new to this list, I came here from the github Spotlight page about
> support and feedback. Questions related to what I am asking have popped up
> a couple of times in this list as far as I can see, but the answers do not
> provide what I am looking for.
>
> I am using the statistical back-end, and I am basically trying to
> reconstruct the confidence value of the entities extracted.
>
> I have extracted entities from tweets and as a first experiment I did
> not asked for any threshold confidence. Now I would like to calculate the
> confidence of each results to see how filtering based on that influences
> the quality of some other process I am doing with the entities.
>
> I am now using the formula:
>
> (1 - .5 * percentageofsecondrank) * similarityscore
>
> Based on the fact that confidence increases with similarity score, but
> decreases if the second candidate is also similar.
>
> Is this comparable to what Spotlight uses in
> http://spotlight.dbpedia.org/rest/annotate? Or else what is the formula?
> Does support play a role?
>
> Thanks,
>
> Stefano
>
>
>
>
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