Logician and orator: Learning from the duality between language and knowledge in open domain

Abstract

We propose the task of Open-Domain Information Narration (OIN) as the reverse task of Open Information Extraction (OIE), to implement the dual structure between language and knowledge in the open domain. We then develop an agent, called Orator, to accomplish the OIN task, and assemble the Orator and the recently proposed OIE agent - Logician (Sun et al., 2018) into a dual system to utilize the duality structure with a reinforcement learning paradigm. Experimental results reveal the dual structure between OIE and OIN tasks helps to build better both OIE agents and OIN agents.