“Traditional machine translation is often prone to errors due to decontextualized interpretation, such as translating 'Apple' (company) as 'apple' (fruit), or 'Spring' (coil) as 'spring' (season).”

Root Cause Analysis

Document-level contextual association

O.Translator utilizes the ultra-long context windows of GPT-4 or Claude, referencing thousands of words before and after, or even the entire document, when translating a term. It can determine from context whether 'Bank' refers to a 'financial institution' or a 'riverbank.'

Domain adaptation

The system automatically recognizes the document type. If 'Mouse' appears in an IT technical document, it will never be rendered as 'rodent.'When encountering 'Nut' in a mechanical engineering document, it will be translated as 'nut' (mechanical fastener) rather than 'nut' (edible seed).

Final Solution Summary

It reasons like a human expert, resolving linguistic ambiguity by comprehending the logic of the entire text.