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14 天 RAG:从检索到可信回答

D11 高级索引:父子文档、摘要索引、上下文检索,以及树状聚合与图检索的取舍

  • 同一份语料建了三套索引,检索时你怎么决定走哪一套?You have built three different indexes over the same corpus. How do you decide which one a query goes to?
    国内高频海外高频进阶#index-routing#evaluation#architecture

    分析过程 · 先想清楚再作答

    1. 这题是送分还是丢分,取决于你有没有先反问一句『真的需要三套吗』。上来就答路由策略的人,默认了一个没被验证的前提。
    2. 第一步是承认多数情况下答案是『都不走,走默认那套』。我们在 30 篇语料上把五种索引结构各测一遍,**召回率全部停在 93.8%,没有一种跑赢基线**;唯一动了的是 nDCG@10(块头把它从 0.6438 抬到 0.7218),而两段式的摘要索引还掉到了 87.5%。每种结构补的都是一个特定短板,你没有那个短板时它只带来成本。
    3. 第二步才是路由,而判据不是『哪套准』——那是离线评估该回答的问题,不是运行时能知道的。运行时能拿到的只有**问题的形状**:细节型(答案落在某一段)、概括型(要全库的一个概括)、多跳型(要跨实体串联)。按形状分流,正好对应块级索引、树状聚合索引、图索引。
    4. 实现上就是一个轻量意图分类器,跟前一天的意图路由是同一套东西,不必再造一个。分类结果作为元数据带进请求,方便事后拿评估集回看分错了多少。
    5. 兜底策略要说清楚:分类错了**回落到默认那一套**,不要并行全查一遍再融合。并行看着稳,实际上把延迟和成本按索引套数翻倍,而多出来的那两路大概率一条都进不了上下文预算。
    6. 可预期的追问是『怎么知道分类器分对了』。答案是把路由决策记进日志,定期拿标准答案集回放:对每个问题分别走三套索引,看分类器选的那套是不是指标最好的那套。这是一个能持续跑的离线作业,不需要人工标注。

    How to reason about it · think before answering

    1. Whether this is an easy point or a lost one depends on whether you first ask 'do we actually need three?'. Jumping straight to routing accepts an unverified premise.
    2. Step one is admitting the answer is usually 'none of them — use the default'. Across 30 documents we measured five index structures and every one landed at 93.8% recall, none beating the baseline. The only metric that moved was nDCG@10, which headers lifted from 0.6438 to 0.7218, while the two-stage summary index fell to 87.5%. Each structure patches one specific weakness; without that weakness it is pure overhead.
    3. Step two is routing, and the criterion is not 'which index is more accurate' — that is an offline evaluation question, not something you know at request time. What you do have at request time is the shape of the question: detail-seeking, summarizing, or entity-chaining. Those map onto the chunk index, the tree-summary index and the graph index.
    4. Implementation is a lightweight intent classifier — the same one from the previous day's intent routing, no need to invent another. Carry the decision as request metadata so you can replay it later.
    5. Spell out the fallback: on a misclassification, fall back to the default index rather than fanning out across all three and fusing. Fan-out looks safe but multiplies latency and cost by the number of indexes, and the extra routes usually never make it into the context budget anyway.
    6. Expect 'how do you know the classifier is right'. Log every routing decision and replay the golden set periodically: run each question through all three indexes and check whether the classifier picked the best-scoring one. It is a standing offline job that needs no human labelling.

    答题要点

    • 先反问是否真需要三套:实测五种索引结构召回率全部持平在 93.8%,没有对应短板就是纯成本。
    • 运行时的判据是问题的形状——细节型、概括型、多跳型,分别对应块级、树状摘要、图索引。
    • 复用前一天的意图路由做分类,把路由决策记进请求元数据。
    • 分类错了回落到默认索引,不要并行全查再融合——延迟和成本按套数翻倍。
    • 用标准答案集定期回放,检验分类器选的那套是不是指标最好的那套。

    Key points

    • First challenge the premise: all five index structures landed at the same 93.8% recall in our measurement, so an index without a matching weakness is pure cost.
    • At request time the usable signal is question shape — detail, summary, or entity-chaining — mapping to chunk, tree-summary and graph indexes.
    • Reuse the previous day's intent router for classification and record the routing decision as request metadata.
    • Fall back to the default index on misclassification instead of fanning out and fusing, which multiplies latency and cost.
    • Replay the golden set periodically to check whether the classifier picks the best-scoring index.