Do OpenAI Embeddings Maintain Sentence Similarity Across Languages?

Below is some information from the OpenAI documentation on embeddings that you might find useful. While the docs don’t explicitly focus on cross-lingual use cases, they describe embeddings as measures of text relatedness regardless of the language. In practice, this means that if two sentences from different languages have the same meaning, their embeddings may be close in the embedding space. However, it’s always a good idea to run some tests on your specific use case.

You can refer to the official embeddings documentation for more details on how embeddings work and their applications:

OpenAI Embeddings Documentation

Additionally, the sections on what embeddings are and how text search is implemented using cosine similarity might shed light on their behavior across different types of text. Keep in mind that while the underlying mechanisms suggest that similar concepts can be captured regardless of language, confirming this with targeted experiments is recommended for your project.