  Syntactic parsers perform poorly in prediction of Argument-Cluster
Coordination (ACC). We change the PTB representation of ACC to be more suitable
for learning by a statistical PCFG parser, affecting 125 trees in the training
set. Training on the modified trees yields a slight improvement in EVALB scores
on sections 22 and 23. The main evaluation is on a corpus of 4th grade science
exams, in which ACC structures are prevalent. On this corpus, we obtain an
impressive x2.7 improvement in recovering ACC structures compared to a parser
trained on the original PTB trees.
