Triple

T32280227
Position Surface form Disambiguated ID Type / Status
Subject American (wizarding world) E824668 entity
Predicate RappaportsLawEffect P159359 FINISHED
Object strict segregation between magical and No-Maj communities LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: strict segregation between magical and No-Maj communities | Statement: [American (wizarding world), RappaportsLawEffect, strict segregation between magical and No-Maj communities]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: RappaportsLawEffect
Context triple: [American (wizarding world), RappaportsLawEffect, strict segregation between magical and No-Maj communities]
  • A. providesEffect
    Indicates that one entity causes, delivers, or produces a particular effect or outcome on another entity.
  • B. canonicalEffect chosen
    Indicates the standard or primary effect that an action, event, or entity is typically understood to produce.
  • C. hasLegalEffect
    Indicates that an action, document, or condition produces recognized legal consequences or enforceable rights and obligations.
  • D. repealEffect
    Indicates that one legal act or decision nullifies, cancels, or removes the force or applicability of another.
  • E. legalEffectIfAdopted
    Indicates that a specified legal effect or consequence will occur if a particular proposal, rule, or measure is formally adopted.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f3490f404081908450db66884f4334 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bcc7edfc81909d0008fa9364de54 completed May 3, 2026, 3:11 a.m.
PD Predicate disambiguation batch_69f6ba6cef208190bc5cd43d96127004 completed May 3, 2026, 3:01 a.m.
Created at: May 1, 2026, 12:43 a.m.