Here , the PET and GR kernel perform similar : this is different from the results of ( Nguyen et al. , 2009 ) where GR performed much worse than PET for ACE data .
convolution kernels on constituent dependency and sequential structures for relation extraction
Truc-Vien T Nguyen Alessandro Moschitti Giuseppe Riccardi
As in the undersampled system , when the data is balanced , SqGRW ( sequence kernel on dependency tree in which grammatical relations are inserted as intermediate nodes ) achieves the best recall . Here , the PET and GR kernel perform similar : this is different from the results of ( Nguyen et al. , 2009 ) where GR performed much worse than PET for ACE data . This exemplifies the difference in the nature of our event annotations from that of ACE relations .
Here , the PET and GR kernel perform similar : this is different from the results of ( @@CITATION ) where GR performed much worse than PET for ACE data .