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Do there exist dictionaries containing

  • lists of many different specific, not general, definitions of a word x

  • lists of many detailed definitions or examples of a word y

  • Venn diagrams showing which definitions are in:

  • definition numbers xy⁻¹

  • definition numbers in x⁻¹ ∩ y

  • definition numbers in xy?

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    Can you provide an example of what kind of entry you envision in that dictionary? I think you’re interested in stuff like Latent Semantic Analysis (en.m.wikipedia.org/wiki/Latent_semantic_analysis) and the cosin similarity and Euclidean distance of word vectors (en.m.wikipedia.org/wiki/Word2vec). And maybe some context on how the question came about could help to provide a satisfactory answer. Thanks.
    – Julius H.
    Jul 30, 2023 at 16:15
  • I think an ontology like Cyc or Yago might fulfill your requirements better than a dictionary.
    – prash
    Aug 3, 2023 at 18:19
  • You may also be interested in semantic maps.
    – Keelan
    Aug 4, 2023 at 6:35
  • [English correction: Do there exist dictionaries is not idiomatic. Are there any dictionaries that x. Or: Do dictionaries exist that x.] A dictionary of semantic traits in words.
    – Lambie
    Sep 2, 2023 at 16:49
  • The meaning of words is analyzed using what are called "semantic traits".
    – Lambie
    Dec 31, 2023 at 19:16

1 Answer 1

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I believe to understand what Samuel is asking for, and maybe I have a similar mental image of the issue. Word vectors have fixed (and not too large) size and components of type float. A lexicon (or dictionary) entry of a word may be seen as a set of properties the referent of the word has. The set of all properties (all named objects can have) is incredibly large, so it's not suitable to represent a word by a gigantic binary vector (or possibly a vector of floats -- when one allows fuzzy properties) with only a small number of components of value 1. So let's assume the lexicon/dictionary consists of labelled sets of properties (represented by integers which are in general very large). It then makes sense to consider the semantic similarity between two words as the size of the intersection of their property sets.

The fixed-size word vectors in turn can be considered as dimensionally reduced representations of the (gigantic) binary lexicon vectors (which are "few-hot vectors", so to say).

A problem with the above lexicon approach is that the properties are not independent. Furthermore, there is a difference between "contingently not having a property" and "non-applicable properties" an object just cannot have. So three values would be more appropriate: 1 for true, null for not applicable, -1 for false.

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  • [I believe I understand, not to understnd]
    – Lambie
    Dec 31, 2023 at 19:13

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