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I have been looking for what I believe would be a very valuable resource in language construction. Ideally, this would be a full-size dictionary, where every description is a short list of words that approximate the meaning.

Ex:

Sleep: Still, Human, State, Noun.

Or something like this? Seems like this could be a good guide to creating more complex portmanteau words from a smaller base.

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You are probably thinking about WordNet, where a synset is a set of words with exactly the same (not just approximate) meaning. But WordNet is much more than this, it also contains informations about relations of hypernym, hyponymy and more...

The original Princeton WordNet was created for English, but there are WordNets (of different sizes, quallity and level of usefulness) for many different languages.

Modern take on the idea is the approximation of semantic closeness in word embeddings models, which has the advantage that it needs "just" a big corpus and no human annotation (and a disadvantage that lacking human proofreading, it contains a lot of errors). See e.g. here (disclaimer: I am the author of that webpage and models).

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  • Your website is very cool! I like the data visualization. WordNet is close to what I was thinking. It's a bit general (Soldier = noun + person), but a great start. Thank you for that resource. Apr 13, 2022 at 2:24
  • @chaseleffers not that soldier is not the best example, because it does not have exactl equivalents. But if you look at the hypernyms, you see the word is a hyponym of enlisted person, serviceman, military man, man, military personnel and a hypernym of cannon fodder,, cavalryman, trooper, flanker, etc, etc... which gives quite a good notion of the meaning Apr 13, 2022 at 15:28
  • I didn't see the hypernym section of the wordnet. Yeah, that's a great resource. Apr 13, 2022 at 20:23
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Looking for a controlled vocabulary to bootstrap the semantics of a conlang brings Natural Semantic Metalanguage (NSM) by Anna Wierzbicka and other authors to my mind. I'm not sure how far any language description in NSM is really worked out and written down, but it may give you a starter for thought.

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  • That is a good resource to check out. Seems like the NSM is very functionally-focused in some senses, but also somewhat specific in other cases, like the space and time sections. I guess it makes sense that those would be the most universal concepts in language. Seems like any language that wants to be intuited by people would need to easily confer the meaning of those semantic primes Apr 13, 2022 at 2:31

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