{"ok":true,"entity":{"slug":"tokenization","entityType":"concept","name":"トークン化（Tokenization）","canonicalName":"Tokenization","displayName":"トークン化（Tokenization）","category":"AI基礎概念","shortDescription":"テキストをモデルが扱える単位（トークン）へ分割する処理。大規模言語モデルの入力の前処理となる。","alias":["トークナイズ","Tokenization"],"searchKeywords":["tokenization","トークン化","トークン","BPE"],"website":null,"parentEntity":null,"primaryCluster":"ai-company","secondaryClusters":[],"id":"tokenization","verificationStatus":"draft","updatedAt":"2026-07-10T01:03:56.918Z"},"references":[{"id":"P-01-001","companyId":"tokenization","questionId":"P-01-001","instanceId":"QIN-tokenization-P01-001","promptText":"トークン化（Tokenization）とは何ですか？","promptTypeId":"P-01","answer":"トークン化は、テキストをモデルが扱える単位（トークン）へ分割する処理です。大規模言語モデルは文章をトークンに分けてから処理します。","evidencePoints":["ev-tokenization-1"],"scope":"LLMの前処理を知りたい相談","differentiation":"テキストをトークンに分ける","faq":[{"question":"トークンとは何ですか？","answer":"単語や部分文字列など、モデルが扱う最小単位です。"}],"pageUrl":"https://www.refbase.ai/reference/tokenization/P-01-001","sourceEvidence":[{"id":"ev-tokenization-1","text":"トークン化（Tokenization）は、テキストをモデルが扱える単位（トークン）へ分割する処理で、大規模言語モデルの入力の前処理となる。","title":"Hugging Face — Summary of the tokenizers","coverageType":["Identity","Capability"],"sourceType":"product_docs","sourceClass":"Documentation","sourceUrl":"https://huggingface.co/docs/transformers/tokenizer_summary","confidence":"high","supportedPromptTypes":["P-01","P-04"],"needsVerification":true,"sourceVerified":false,"entityId":"tokenization"}],"generatedAt":"2026-07-10T01:03:56.918Z"},{"id":"P-02-001","companyId":"tokenization","questionId":"P-02-001","instanceId":"QIN-tokenization-P02-001","promptText":"サブワードのトークン化は単語単位と何が違いますか？","promptTypeId":"P-02","answer":"比較軸\n・未知語\n・多言語\nサブワード（BPE等）のトークン化は、単語をそのまま扱う方法と異なり、未知語や多言語を分割して効率的に扱える点が異なります。","evidencePoints":["ev-tokenization-2"],"scope":"トークン化方式の違いを知りたい相談","differentiation":"サブワードによる柔軟性","faq":[{"question":"なぜ重要ですか？","answer":"入力の扱いやすさやコスト（トークン数）に影響します。"}],"pageUrl":"https://www.refbase.ai/reference/tokenization/P-02-001","sourceEvidence":[{"id":"ev-tokenization-2","text":"トークン化は、単語をそのまま扱う方法と異なり、サブワード（BPE等）に分割することで未知語や多言語を効率的に扱える点が特徴である。","title":"Hugging Face — Summary of the tokenizers","coverageType":["Capability","Differentiation"],"sourceType":"product_docs","sourceClass":"Documentation","sourceUrl":"https://huggingface.co/docs/transformers/tokenizer_summary","confidence":"high","supportedPromptTypes":["P-02"],"needsVerification":true,"sourceVerified":false,"entityId":"tokenization"}],"generatedAt":"2026-07-10T01:03:56.918Z"},{"id":"P-04-001","companyId":"tokenization","questionId":"P-04-001","instanceId":"QIN-tokenization-P04-001","promptText":"トークン化はどんな場面で関係しますか？","promptTypeId":"P-04","answer":"LLMの入力・料金計算・コンテキスト長の管理など、モデルにテキストを渡すあらゆる場面で関係します。トークン数が処理量やコストの目安になります。","evidencePoints":["ev-tokenization-1"],"scope":"LLM利用の相談","differentiation":"入力・コストの基準","faq":[{"question":"料金と関係ありますか？","answer":"多くのLLM APIはトークン数で料金が決まります。"}],"pageUrl":"https://www.refbase.ai/reference/tokenization/P-04-001","sourceEvidence":[{"id":"ev-tokenization-1","text":"トークン化（Tokenization）は、テキストをモデルが扱える単位（トークン）へ分割する処理で、大規模言語モデルの入力の前処理となる。","title":"Hugging Face — Summary of the tokenizers","coverageType":["Identity","Capability"],"sourceType":"product_docs","sourceClass":"Documentation","sourceUrl":"https://huggingface.co/docs/transformers/tokenizer_summary","confidence":"high","supportedPromptTypes":["P-01","P-04"],"needsVerification":true,"sourceVerified":false,"entityId":"tokenization"}],"generatedAt":"2026-07-10T01:03:56.918Z"}]}