Our training examples are similar to the data created for pseudodisambiguation , the usual evaluation task for SP models ( Erk , 2007 ; Keller and Lapata , 2003 ; Rooth et al. , 1999 ) .
inducing a semantically annotated lexicon via embased clustering
Mats Rooth Stefan Riezler Detlef Prescher Glenn Carroll Franz Beil
Similarity-smoothed models can make use of the regularities across similar verbs , but not the finergrained stringand token-based features . Our training examples are similar to the data created for pseudodisambiguation , the usual evaluation task for SP models ( Erk , 2007 ; Keller and Lapata , 2003 ; Rooth et al. , 1999 ) . This data consists of triples ( v , n , n â² ) where v , n is a predicateargument pair observed in the corpus and v , n â² has not been observed .
Our training examples are similar to the data created for pseudodisambiguation , the usual evaluation task for SP models ( Erk , 2007 ; Keller and Lapata , 2003 ; @@CITATION ) .