- From: Nathan <nathan@webr3.org>
- Date: Tue, 02 Feb 2010 16:54:35 +0000
- To: Matthias Samwald <samwald@gmx.at>
- CC: Davide Palmisano <davide@asemantics.com>, public-lod@w3.org
Matthias Samwald wrote: > Nathan wrote >> Quite sure the results speak for themselves + glad that so much useful >> information can be extracted from text all ready. > > The results look good indeed. It even passed the FOAF test! > > Can you estimate the ratio of contributions from Zemanta / contributions > from OpenCalais? Does one source add more than the other? Does the ratio > vary significantly between different texts? > Zemanta is more precise, OpenCalais is more verbose; results vary depending on the subject matter and each documents content - in all honesty there is no way to say one is better than the other, but I can say that both combined is as good as you can get for now. Noted that Kingsley mentioned the Sponger Middleware for virtuoso, this would allow you to do the same afaik, but faster and with the option of adding in more sponger cartridges for virtually any third party api's + with the extensive list of cartridges already included it's definitely an option worth looking in to - and ultimately the fastest / most reliable. fyi: i ran your source text through the combination system and here's what it brings back: http://dbpedia.org/resource/Nervous_system http://dbpedia.org/resource/Albizia http://dbpedia.org/resource/5-HT1A_receptor http://dbpedia.org/resource/Serotonin http://dbpedia.org/resource/Albizia_julibrissin http://dbpedia.org/resource/Serotonergic http://dbpedia.org/resource/Parasympathetic_nervous_system http://dbpedia.org/resource/Neurochemistry http://dbpedia.org/resource/Biochemistry http://dbpedia.org/resource/Neurotransmitter http://dbpedia.org/resource/Physiology http://dbpedia.org/resource/Biology regards, Nathan
Received on Tuesday, 2 February 2010 16:55:15 UTC