ConceptNet: a practical commonsense reasoning toolkit

ConceptNet begins with a practical question: can ordinary knowledge gathered from ordinary people become usable infrastructure for software? Roughly fifty extraction rules transformed Open Mind Common Sense sentences into relations; MontyLingua parsed the language, and later normalization merged grammatical variants, reconciled vocabulary, and added thematic links. ConceptNet 2.0 contained about 1.6 million assertions over 300,000 nodes, drawn from some 700,000 sentences contributed by more than 14,000 people. Its toolkit supported contextual neighborhoods, analogy, projection, topic gisting, classification, novel-concept detection, and affect sensing. The paper is equally clear about the unfinished work: coverage was uneven, paraphrases fragmented the evidence, and most assertions appeared only once. Its human evaluation described the earlier 1.2 network, not the new thematic links in 2.0. Built with Push Singh, a close friend and collaborator on Open Mind Common Sense, it is the most-cited work in this record.