The Latent Structure of Dictionaries. (18th July 2016)

• Record Type: Journal Article
• Authors: Vincent‐Lamarre, Philippe; Massé, Alexandre Blondin; Lopes, Marcos; Lord, Mélanie; Marcotte, Odile; Harnad, Stevan
• Is Part Of: Topics in cognitive science. Volume 8:Number 3(2016:Jul.)
• Page Start: 625
• Page End: 659
• Publication Date: 2016-07-18
• Subjects: Symbol grounding -- Dictionary definition -- Meaning -- Categorization -- Dual coding -- Graph theory -- Mental lexicon -- Lexical semantics; Cognitive science -- Periodicals; Cognitive Science -- Periodicals; 153.05
• DOI: 10.1111/tops.12211
• Languages: English
• ISSNs: 1756-8757

Abstract

Abstract: How many words—and which ones—are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns out to be its Core, a "Strongly Connected Subset" of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites . The size of the smallest set of words that can define all the rest—the graph's "minimum feedback vertex set" or MinSet —is about 1% of the dictionary, about 15% of the Kernel, and part‐Core/part‐Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual‐code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition. Abstract : Only about 1% of the words in a dictionary are needed to define all the rest. These "grounding" words turn out to be more frequent and are learned earlier than the rest. In principle, they are the only words whose meanings we need to learn from direct experience. Then language can recombine them to define and describe everything else.