I recently gave a talk at the Allen Institute for Artificial Intelligence (AI2) on my work in explanation-centered inference for solving standardized science exams. This talk is a good high-level introduction to three recent papers on understanding the kinds of knowledge and inference required to build explanations (COLING 2016), our work in building a very large corpus of semi-structured explanations (the largest I’m aware of) to help us learn how to combine large amounts of information for inference (LREC 2018), and examining this corpus for common explanatory patterns that would help us make the task of building new explanations easier (AKBC 2017).
We’re very excited about this new knowledge resource that’s been two years in the making, and it’s potential for exploring explanation-centered inference. The Worldtree corpus is available here, at the Explanation Bank!