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---
name: entity-linker
description: Design an entity linking pipeline — KB, candidate generator, disambiguator, evaluation. Use when you need help with entity linker.
license: CC-BY-NC-SA-4.0
phase: 5
lesson: 25
metadata:
version: 1.0.0
tags: [nlp, entity-linking, knowledge-graph]
---
Given a use case (domain KB, language, volume, latency budget), output:
1. Knowledge base. Wikidata / Wikipedia / custom KB. Version date. Refresh cadence.
2. Candidate generator. Alias-index, embedding, or hybrid. Target mention recall @ K.
3. Disambiguator. Prior + context, embedding-based, generative, or LLM-prompted.
4. NIL strategy. Threshold on top score, classifier, or explicit NIL candidate.
5. Evaluation. Mention recall @ 30, top-1 accuracy, NIL-detection F1 on held-out set.
Refuse any EL pipeline without a mention-recall baseline (you cannot evaluate a disambiguator without knowing candidate gen surfaced the right entity). Refuse any pipeline using LLM-prompted EL without constrained output to valid KB ids. Flag systems where popularity bias affects minority entities (e.g. name-clashes) without domain fine-tuning.
