Building Multilingualism with Claude and Divooka App Platform
There is an interesting theory in linguistics, namely the arbitrariness of the linguistic sign : there is no inherent or necessary connection between a word's sound (the signifier) and its meaning (the signified). Background The arbitrariness of the linguistic sign - a fundamental principle of linguistics associated with Swiss linguist Ferdinand de Saussure - dictates that there is no inherent or…
Linguists have long debated the nature of the connection between word sounds and their meanings. Ferdinand de Saussure, a Swiss linguist, established the concept of arbitrariness of the linguistic sign in his 1916 work, arguing that there is no inherent or necessary relationship between a word's sound (the signifier) and its meaning (the signified).
This means that different languages can express the same concept using completely different pronunciations. For instance, the same animal might be called "dog" in English, "chien" in French, "Hund" in German, "inu" in Japanese, and "gǒu" in Mandarin Chinese. While arbitrariness does not imply complete randomness, certain linguistic phenomena like onomatopoeia, sound symbolism, and historical language relationships add structure to the process.
The deeper implication is that meaning is established through social convention rather than any intrinsic link between sound and concept. Motivated by his fascination with languages and his passion for building language-related tools, the author decided to create a multilingual dictionary. He faced the challenge of providing fast and reliable translations in a user-friendly format.
After exploring existing resources, he realized that the current website often became unavailable or slow, prompting him to consider building his own solution. Leveraging Claude through Divooka App Platform's MCP connector, the author successfully developed the Multilingualism website. The entire application was built using Claude, with Claude handling the requirements, translation pipeline, interface development, and iteration.
This project served as both a practical test for Divooka App Platform and an experiment in AI-assisted development. The translation dataset was sourced primarily from English Wiktionary, processed through a Python pipeline that prioritized common words, filled missing entries, and compared machine-generated results with human-controlled samples.
The final dataset contained translations for 9,852 English words and phrases across 108 languages, organized in JSON files and hosted on the jsDelivr CDN for fast loading without the need for a backend server.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
