For these rules, we refer to the conversion of the Penn Treebank into dependency structures used in the CoNLL 2008 Shared Task , and mark the heads of these rules in a way that will arrive at a compatible dependency backbone.

the CoNLL shared task dependency structures, minor systematic differences still exist for some phenomena.

To evaluate the performance of our different dependency parsing models, we tested our approaches on several dependency treebanks for English in a similar spirit to the CoNLL 2006-2008 Shared Tasks .

In previous years of CoNLL Shared Tasks , several datasets have been created for the purpose of dependency parser evaluation.

The same dataset has been used for the domain adaptation track of the CoNLL 2007 Shared Task .

In the meantime, successful continuation of CoNLL Shared Tasks since 2006 (Buchholz and Marsi, 2006; Nivre et al., 2007a; Surdeanu et al., 2008) have witnessed how easy it has become to train a statistical syntactic dependency parser provided that there is annotated treebank.

In recent years, two statistical dependency parsing systems, MaltParser (Nivre et al., 2007b) and MS TParser (McDonald et al., 2005b), representing different threads of research in data-driven machine learning approaches have obtained high publicity, for their state-of-the-art performances in open competitions such as CoNLL Shared Tasks .

PB is a standard corpus for SRL evaluation and was used in the CoNLL SRL shared tasks of 2004 (Carreras and Marquez, 2004) and 2005 (Carreras and Marquez, 2005).

The CoNLL shared tasks of 2004 and 2005 were devoted to SRL, and studied the influence of different syntactic annotations and domain changes on SRL results.

Supervised clause detection was also tackled as a separate task, notably in the CoNLL 2001 shared task (Tjong Kim Sang and Dejean, 2001).

Following the CoNLL shared task from 2000, we use sections 15-18 of the Penn Treebank for our labeled training data for the supervised sequence labeler in all experiments (Tjong et al., 2000).

The chunker’s accuracy is roughly in the middle of the range of results for the original CoNLL 2000 shared task (Tjong et al., 2000) .

For our experiment on domain adaptation, we focus on NP chunking and POS tagging, and we use the labeled training data from the CoNLL 2000 shared task as before.