In 2005, the PropBank project at the University of Pennsylvania added semantic role labels to the Penn Treebank, creating the first large-scale semantic annotation resource compatible with a major syntactic treebank. By using numbered arguments and verb-specific frame files, PropBank enabled semantic role labeling as a standard NLP task and influenced the development of modern semantic understanding systems.
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About the author: Michael Brenndoerfer
All opinions expressed here are my own and do not reflect the views of my employer.
Michael currently works as an Associate Director of Data Science at EQT Partners in Singapore, where he drives AI and data initiatives across private capital investments.
With over a decade of experience spanning private equity, management consulting, and software engineering, he specializes in building and scaling analytics capabilities from the ground up. He has published research in leading AI conferences and holds expertise in machine learning, natural language processing, and value creation through data.
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