Abstract:

This talk outlines my research trajectory in language understanding and reasoning. I begin with event extraction through question-answering techniques, followed by constructing event schemas. Subsequently, I investigate the translation of natural language into symbolic representations to facilitate faithful reasoning. Currently, my work explores training language models using both natural language and knowledge graphs, as well as evaluating narratives through knowledge graphs.

Bio:

Tianyi Zhang is a visiting scholar at the University of Bonn, supervised by Prof. Lucie Flek. Her research focuses on extracting entity-relationship knowledge from text and reasoning with structured and symbolic representations.

She received master’s degrees in Data Science and in Learning Science and Technology from the University of Pennsylvania.