Output

This benchmark for recipe understanding in autonomous agents aims to support progressing the domain of natural language understanding by providing a setting in which performance can be measured on the everyday human activity of cooking. For this goal, the benchmark provides a number of recipes written in natural (human) English that should be converted to a procedural semantic network of cooking operations that can be interpreted and executed by autonomous agents.  The full benchmark has been made available standalone and as part of the Babel toolkit. Both options provide the same benchmark functionalities, but the Babel toolkit also provides the option of extending the system.

“The ultimate purpose of social sciences is to furnish causal explanations of classes of observable events, which are, at least in part, generated by individual and collective agency/action.” [1] The aim of a digital assistant for social history research is therefore to support social scientists with the construction of such causal explanations for observable events, also theories or hypotheses.