Loglan is a logical constructed language originally designed for linguistic research, particularly for investigating the Sapir–Whorf hypothesis. The language was developed beginning in 1955 by Dr. James Cooke Brown with the goal of making a language so different from natural languages that people learning it would think in a different way if the hypothesis were true. In 1960, Scientific American published an article introducing the language. Loglan is the first among, and the main inspiration for, the languages known as logical languages, which also includes Lojban.
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Loglan is a logical constructed language originally designed for linguistic research, particularly for investigating the Sapir–Whorf hypothesis. The language was developed beginning in 1955 by Dr. James Cooke Brown with the goal of making a language so different from natural languages that people learning it would think in a different way if the hypothesis were true. In 1960, Scientific American published an article introducing the language. Loglan is the first among, and the main inspiration for, the languages known as logical languages, which also includes Lojban.
Brown founded The Loglan Institute (TLI) to develop the language and other applications of it. He always considered the language an incomplete research project, and although he released many publications about its design, he continued to claim legal restrictions on its use. Because of this, a group of his followers later formed the Logical Language Group to create the language Lojban along the same principles, but with the intention to make it freely available and encourage its use as a real language.
via Wikipedia infobox
Welcome to Loglan.org
This page is the starting point for information about the constructed human language known as Loglan.
loglan.org →Link to the official site · 18,318 chars · not written by Vinony
CALS: Language: Loglan
cals.info →Link to a page describing this subject · 15,091 chars · not written by Vinony
via Wikidata · CC0
via Wikidata sitelinks · CC0
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).