---
title: "Crowdsourced taxonomy verification: A feedback-driven framework for refining knowledge graph relationships via online search interactions"
url: https://daily.dev/posts/crowdsourced-taxonomy-verification-a-feedback-driven-framework-for-refining-knowledge-graph-relatio-npizmg5us
source_url: https://engineering.grab.com/crowdsourced-taxonomy-verification
type: article
source: "Grab Tech Blog"
published: 2026-07-31T02:15:44.100Z
updated: 2026-07-31T04:29:44.672Z
reading_time: 12
upvotes: 0
comments: 0
language: en
---

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# Crowdsourced taxonomy verification: A feedback-driven framework for refining knowledge graph relationships via online search interactions

**[Grab Tech Blog](https://daily.dev/sources/grab)** · 12 min read · 0 upvotes · 0 comments

## Summary

Grab Engineering presents a feedback-driven framework for verifying knowledge graph (KG) relationships at scale in dynamic domains like food delivery. The system treats unverified LLM-generated graph edges as hypotheses, injects them into live search results using an exploration vs. exploitation strategy (multi-armed bandit), and uses weighted user interaction signals (clicks, purchases, dwell time) to promote or prune candidate edges. The four-step loop covers hypothesis generation, candidate injection, signal aggregation, and graph topology updates. A food delivery case study illustrates how a candidate parent-child link like 'Noodle Soup → Dry Mee Pok' gets validated through real user traffic without manual curation. Future work includes hierarchical confidence tiers with a state machine (proposed → shadow → canary → production) and adversarial/spam resistance mechanisms.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://engineering.grab.com/crowdsourced-taxonomy-verification>

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