Proposition Knowledge Graphs

Open Information Extraction (Open IE) is a promising approach for unrestricted Information Discovery (ID). While Open IE is a highly scalable approach, allowing unsupervised relation extraction from open domains, it currently has some limitations. First, it lacks the expressiveness needed to properly represent and extract complex assertions that are abundant in text. Second, it does not consolidate the extracted propositions, which causes simple queries above Open IE assertions to return insufficient or redundant information. To address these limitations, we propose in this position paper a novel representation for ID – Propositional Knowledge Graphs (PKG). PKGs extend the Open IE paradigm by representing semantic inter-proposition relations in a traversable graph. We outline an approach for constructing PKGs from single and multiple texts, and highlight a variety of high-level applications that may leverage PKGs as their underlying information discovery and representation framework.