The WebQuestions dataset of questions and answers. Part of the SEMPRE project
A state-of-the-art resource of entailment rules
between natural language predicates, containing millions of entailment rules. The resource contains a knowledge-base obtained by applying the
global algorithm presented in the ACL 2012 paper "Efficient Tree-based Approximation for Entailment Graph Learning", and also a knowledge-base constructed
using a local entailment classifier described in my thesis (to be published soon).
All data required for performing the experiment described in Section 5.1 of the paper: "Global Learning of Typed Entailment Rules"
A resource of 30,000 entailment rules between typed predicates, as described in the paper: "Global Learning of Typed Entailment Rules"
Gold standard healthcare graphs described in "Global Learning of Focused Entailment Graphs", ACL 2010, and "Learning Entailment Relations by Global Graph Structure Optimization", CL 38(1).