# Reasoning Over Virtual Knowledge Bases With Open Predicate Relations Source: [Reasoning Over Virtual Knowledge Bases With Open Predicate Relations]() Collection index: [llms.txt]() Data updated: 2025-10-25T23:18:37.363Z Authors: Haitian Sun, Pat Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen Published: 2021-02-14T01:29:54.000Z ## Abstract We present the Open Predicate Query Language (OPQL); a method for constructing a virtual KB (VKB) trained entirely from text. Large Knowledge Bases (KBs) are indispensable for a wide-range of industry applications such as question answering and recommendation. Typically, KBs encode world knowledge in a structured, readily accessible form derived from laborious human annotation efforts. Unfortunately, while they are extremely high precision, KBs are inevitably highly incomplete and automated methods for enriching them are far too inaccurate. Instead, OPQL constructs a VKB by encoding and indexing a set of relation mentions in a way that naturally enables reasoning and can be trained without any structured supervision. We demonstrate that OPQL outperforms prior VKB methods on two different KB reasoning tasks and, additionally, can be used as an external memory integrated into a language model (OPQL-LM) leading to improvements on two open-domain question answering tasks. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Open-domain Question Answering on ComplexWebQuestions (CWQ) (dev)](): Open-domain Question Answering; ComplexWebQuestions (CWQ) (dev); Accuracy: 41.1. ## Original sources and implementation [Original paper]() [PDF]()