A Data-Driven Study of Commonsense Knowledge using the ConceptNet Knowledge Base

TL;DR

This paper conducts a comprehensive empirical and structural analysis of ConceptNet, a large commonsense knowledge base, revealing deep relation substructures and advancing understanding of commonsense knowledge in AI.

Contribution

It introduces a systematic, data-driven methodology using graph embeddings and clustering to analyze and interpret commonsense knowledge in ConceptNet at scale.

Findings

Revealed deep substructures in ConceptNet relations

Provided data-driven insights into the meaning of 'context'

Demonstrated how computational methods can understand complex psychological phenomena

Abstract

Acquiring commonsense knowledge and reasoning is recognized as an important frontier in achieving general Artificial Intelligence (AI). Recent research in the Natural Language Processing (NLP) community has demonstrated significant progress in this problem setting. Despite this progress, which is mainly on multiple-choice question answering tasks in limited settings, there is still a lack of understanding (especially at scale) of the nature of commonsense knowledge itself. In this paper, we propose and conduct a systematic study to enable a deeper understanding of commonsense knowledge by doing an empirical and structural analysis of the ConceptNet knowledge base. ConceptNet is a freely available knowledge base containing millions of commonsense assertions presented in natural language. Detailed experimental results on three carefully designed research questions, using state-of-the-art unsupervised graph representation learning ('embedding') and clustering techniques, reveal deep substructures in ConceptNet relations, allowing us to make data-driven and computational claims about the meaning of phenomena such as 'context' that are traditionally discussed only in qualitative terms. Furthermore, our methodology provides a case study in how to use data-science and computational methodologies for understanding the nature of an everyday (yet complex) psychological phenomenon that is an essential feature of human intelligence.