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Arjen de Vries (arjen) - 11 years ago 2014-06-12 06:54:00
arjen.de.vries@cwi.nl
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mypaper-final.tex
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@@ -295,25 +295,25 @@ that can be useful for initial KB-dossier are annotated as
 
%distinction made between vital and relevant.
 
 
\subsection{Breakdown of results by document source category}
 
 
%The results of the different entity profiles on the raw corpus are
 
%broken down by source categories and relevance rank% (vital, or
 
%relevant).  
 
In total, the dataset contains 24162 unique entity-document
 
pairs, vital or relevant; 9521 of these have been labelled as vital,
 
and the remaining 17424 as relevant.
 
All documents are categorized into 8 source categories: 0.98\%
 
arxiv(a), 0.034\% classified(c), 0.34\% forum(f), 5.65\% linking(l),
 
11.53\% mainstream-news(m-n), 18.40\% news(n), 12.93\% social(s) and
 
11.53\% main\-stream-news(m-n), 18.40\% news(n), 12.93\% social(s) and
 
50.2\% weblog(w). We have regrouped these source categories into three
 
groups ``news'', ``social'', and ``other'', for two reasons: 1) some groups
 
are very similar to each other. Mainstream-news and news are
 
similar. The reason they exist separately, in the first place,  is
 
because they were collected from two different sources, by different
 
groups and at different times. we call them news from now on.  The
 
same is true with weblog and social, and we call them social from now
 
on.   2) some groups have so small number of annotations that treating
 
them independently does not make much sense. Majority of vital or
 
relevant annotations are social (social and weblog) (63.13\%). News
 
(mainstream +news) make up 30\%. Thus, news and social make up about
 
93\% of all annotations.  The rest make up about 7\% and are all
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