The CoNLL 2007 shared task on dependency parsing

The Conference on Computational Natural Language Learning features a shared task, in which participants train and test their learning systems on the same data sets. In 2007, as in 2006, the shared task has been devoted to dependency parsing, this year with both a multilingual track and a domain adaptation track. In this paper, we define the tasks of the different tracks and describe how the data sets were created from existing treebanks for ten languages. In addition, we characterize the different approaches of the participating systems, report the test results, and provide a first analysis of these results

Adapting the RASP System for the CoNLL07 Domain-Adaptation Task

We describe our submission to the domain adaptation track of the CoNLL07 shared task in the open class for systems using external resources. Our main finding was that it was very difficult to map from the annotation scheme used to prepare training and development data to one that could be used to effectively train and adapt the RASP system unlexicalized parse ranking model. Nevertheless, we were able to demonstrate a significant improvement in performance utilizing bootstrapping over the PBIOTB data.