2024-12-03 · nlp, japanese
Tokenizer Choices for Japanese Product Reviews
Japanese product reviews stress tokenization pipelines. Morphological analyzers handle conjugation well but can be slow on large batches. Subword models generalize to rare words yet may split product names awkwardly.
In NLP for Japanese Text, learners run the same classifier with three tokenization paths and document precision/recall deltas. We emphasize error analysis: pull twenty false positives and label whether the mistake is linguistic, entity-specific, or label noise.
For deployment, latency and dictionary maintenance matter as much as offline accuracy. We discuss when a simpler TF-IDF baseline is the right production choice — a point some teams skip when chasing transformer benchmarks.
This post reflects cohort discussions; your domain may need custom entity dictionaries or romanized brand tokens.