<p>&quot;Made up of pieces&quot; makes me think of a permutational approach. Let
<em>kitabo</em> be the root word for &quot;book&quot; and the word for book in language 1 (l1).
Than <em>bokita</em> can be in l2, and <em>taboki</em> in l3, and for l4 you can choose another permutation like <em>kibota</em>. Here, I permuted syllables, you can also choose to permute only the consonants or the vowels.</p>
<p>The short function words may pose a problem, you can have them the same or somehow different for the four languages.</p>
<p>The second task is probably not feasible. Although large language models (LLMs) can now produce stories, they need to be trained on a large amount of data in the target language. Because your four languages are brand new, the data are lacking.</p>

CC BY-SA 4.0
2024-09-21T21:58:51.860Z
2024-09-21T21:58:51.860Z
Sir Cornflakes
<p>This is a software engineering question.</p>
<p>How would you use a script to create not one language but four languages whose words were made up of pieces of words of all four languages, and then make a set of stories for kids in these languages that interrelated everything (and, then, the languages could be studied)?</p>
<p>Thanks.</p>

<engineered-languages>
Construction of sets of languages and stories for kids in those languages
# Construction of sets of languages and stories for kids in those languages

(Asked by: username_0 on 2024-09-21)

This is a software engineering question.

How would you use a script to create not one language but four languages whose words were made up of pieces of words of all four languages, and then make a set of stories for kids in these languages that interrelated everything (and, then, the languages could be studied)?

Thanks.

**Tags:** engineered-languages


---

## 1 answers

### Answer by username_1 on 2024-09-21. Score: 1

"Made up of pieces" makes me think of a permutational approach. Let
*kitabo* be the root word for "book" and the word for book in language 1 (l1).
Than *bokita* can be in l2, and *taboki* in l3, and for l4 you can choose another permutation like *kibota*. Here, I permuted syllables, you can also choose to permute only the consonants or the vowels.

The short function words may pose a problem, you can have them the same or somehow different for the four languages.

The second task is probably not feasible. Although large language models (LLMs) can now produce stories, they need to be trained on a large amount of data in the target language. Because your four languages are brand new, the data are lacking.


---

