Systems for syntactically parsing sentences have long been recognized as a priority in Natural Language Processing. Statistics-based systems require large amounts of high quality syntactically parsed data. Using the XLE toolkit developed at PARC and the LFG Parsebanker interface developed at Bergen, the Parsebank Project at Powerset has generated a rapidly increasing volume of syntactically parsed data. By using these tools, we are able to leverage the LFG framework to provide richer analyses via both constituent (c-) and functional (f-) structures. Additionally, the Parsebanking Project uses source data from Wikipedia rather than source data limited to a specific genre, such as the Wall Street Journal. This paper outlines the process we used in creating a large-scale LFG-Based Parsebank to address many of the shortcomings of previously-created parse banks such as the Penn Treebank. While the Parsebank corpus is still in progress, preliminary results using the data in a variety of contexts already show promise.