CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge

TL;DR

CogNet is a comprehensive knowledge base integrating linguistic, world, and commonsense knowledge using a unified frame-styled architecture, enabling diverse knowledge querying and exploration.

Contribution

The paper introduces CogNet, a novel unified framework that combines three types of knowledge with a consistent representation and integration strategy.

Findings

Integrates over 1,000 semantic frames and 20 million instances.

Includes 90,000+ commonsense assertions.

Provides an accessible online platform for querying and downloading data.

Abstract

In this paper, we present CogNet, a knowledge base (KB) dedicated to integrating three types of knowledge: (1) linguistic knowledge from FrameNet, which schematically describes situations, objects and events. (2) world knowledge from YAGO, Freebase, DBpedia and Wikidata, which provides explicit knowledge about specific instances. (3) commonsense knowledge from ConceptNet, which describes implicit general facts. To model these different types of knowledge consistently, we introduce a three-level unified frame-styled representation architecture. To integrate free-form commonsense knowledge with other structured knowledge, we propose a strategy that combines automated labeling and crowdsourced annotation. At present, CogNet integrates 1,000+ semantic frames from linguistic KBs, 20,000,000+ frame instances from world KBs, as well as 90,000+ commonsense assertions from commonsense KBs. All these data can be easily queried and explored on our online platform, and free to download in RDF format for utilization under a CC-BY-SA 4.0 license. The demo and data are available at http://cognet.top/.