The curious kernels of dictionaries

Grounded kernel

If you don’t know the meanng of a word, you look it up in the dictionary. But what if you don’t know the meaning of any of the words in the definition? Or the meaning of any of the words in the definitions of these defining words? And so on ad infinitum.

This is known as the “symbol grounding problem” and is related to the nature of meaning in language.  The way out of this problem is to assume that we somehow automatically “know” the meaning of a small kernel of words from which all others can be defined.

The thinking is that some words are so closely linked to the object to which they refer that we know their meaning without a definition. Certain individuals, events and  actions apparently fall into this category. These words are called “grounded”.

How this controversial idea might work, we’ll leave for another day.The question we’re pondering today, thanks to Alexandre Blondin Masse at the University of Quebec in Canada is: how small a kernel of grounded words do we need to access the entire dictionary.

We don’t have an answer for you but Blondin Masse and pals have a method based on the concept of reachable set: “a larger vocabulary whose meanings can be learned from a smaller vocabulary through definition alone, as long as the meanings of the smaller vocabulary  are
themselves already grounded”.

The team have even  developed algorithms to compute a reachable set for any given dictionary and from that the size of the grounded kernel.

It has to be said that modern dictionaries already work like this; they are based on a defining vocabulary of about 2000 words from which all others are defined, although this system does not appear to be rigorously enforced, says Blondin Masse and co.

Nobody knows whether 2000 words is close to the theoretical limit for a grounding kernel. But we’ll expect Blondin Masses and pals to tell us soon.

Ref: arxiv.org/abs/0806.3710: How Is Meaning Grounded in Dictionary Definitions?

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5 Responses to “The curious kernels of dictionaries”

  1. Tyler Says:

    fascinating. goes directly to the foundations of thought, math and science as well as the obvious applications to linguistics and critical theory. the most interesting thing I’ve seen here in ages.

  2. Richard Kennaway Says:

    I wonder if they’re aware of the work of Anna Wierzbicka and the Natural Semantic Metalanguage? By entirely different methods, she at one point had reduced the kernel of language to, I think, 11 semantic primes, although since then the NSM has expanded to around 60.

  3. Peter Turney Says:

    This paper is discussed in the blog post Grounding Meaning: Composition versus Abstraction.

  4. Ope Says:

    I supposed a similar idea could be applied to specialized fields of study: what is the smallest set of ideas and concepts required to understand or at least constructively criticize cutting edge work in a field of study?
    What is the relative size of the “grounding kernel” required to make substantive contributions to that field?

  5. CW64 Says:

    Another way to associate meaning with words is to find synonyms. The chances are very likely that one will discover words s/he knows in that group.

    Also, the simplest way to learn a new word, in my experience, is to take an extended definition and reduce it to one or two primary words, which are easier to remember than a long, complicated string of words (many of which, as you state here, are in themselves quite indecipherable). Assuming that a word’s definition is phrased in such a way that defining words are equally unknown, one could then fall back on the synonym. That is one purpose for a thesaurus.

    Minimalism would serve the “grounding kernel” in that both deal with reducing ideas and concepts to their most basic means without losing meaning or the nuances within. People learn best by starting at basic and expanding deeper into specifics. The “grounding kernel” suggests this to be a mandatory means for general education, as long as the approach is a sound one. What works for some might not work for others.

    Truly an interesting article.

    CW64
    http://creatiwriter64.wordpress.com

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