Thanks to everyone for the help yesterday with the statistical endpoint. I'm trying to understand how to tune the tool to get optimal results.
When I used the example text in the demo interface - President Obama called Wednesday on Congress to extend a tax break for students included in last year's economic stimulus package, arguing that the policy provides more generous assistance. A confidence of 0.5 only picked up 'Congress'. Reducing the confidence to 0.3 picked up a lot more stuff - including linking 'Wednesday' to a sports team, which seems bizarre to me. On my own data, which comes from Twitter, I see weird things like mentions of 'police' linking to the musical group The Police, and the word 'celebrate' (in the context of celebrating an anniversary) linking to the Madonna song. If I turn the confidence up, I lose those references, but I also lose 'good' references as well. I feel like whitelisting or blacklisting is the way to go, but I'm having trouble correlating the types I see in my results with the ontology at http://mappings.dbpedia.org/server/ontology/classes/ That ontology particularly confuses me, as it seems very uneven - as an example, under 'Organization', there are classes that make sense to me, like 'Company' and "Sports League', and then oddly specific things like 'Comedy Group' and 'Samba School' at the same level. In my results, there are a mix of types from DBpedia, Schema, and Freebase, and it's not clear to me how I would specify (for example) that I'm interested in people, places, and events, but not musical groups, internet concepts (it always picks up 'http' from embedded links and gives me 'Hypertext Transfer Protocol'), etc. Thanks! Betsey Benagh Boston Fusion Corp. 1 Van de Graaff Drive, Ste 107 Burlington, MA 01803-5176 [email protected] 617-583-5730 x106 (office) 781-367-6720 (mobile)
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