Why Japanese and Korean Text Breaks Standard NLP Pipelines

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Most text processing tools are built around the assumption that words are separated by spaces, an assumption that Japanese and Korean fundamentally violate. Japanese has no word delimiters and requires morphological analysers like MeCab or Sudachi, which can disagree on how to segment the same text. Korean includes spacing but attaches grammatical particles directly to word stems, meaning a simple split() treats the same noun as multiple unrelated tokens. Unicode normalisation differences in Korean Hangul can also cause the same visible text to have varying code point counts, leading to subtle bugs in length calculations. Accurate processing of both languages requires morphological analysis over raw characters, pinned analyser versions, and validation on natively written text rather than translated content.

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