Triple

T4489313
Position Surface form Disambiguated ID Type / Status
Subject Hannah Waterman King E107328 entity
Predicate familyName P18 FINISHED
Object King E280718 NE 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: King | Statement: [Hannah Waterman King, familyName, King]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: King
Context triple: [Hannah Waterman King, familyName, King]
  • A. King
    The King is the reigning male monarch who serves as the head of state of the United Kingdom within its constitutional monarchy system.
  • B. King
    King is a township in the Regional Municipality of York in Ontario, Canada, known for its rural landscapes, rolling hills, and equestrian farms within the Greater Toronto Area.
  • C. King
    The King of Norway is the constitutional monarch and ceremonial head of state in Norway’s parliamentary system.
  • D. King
    King is a prominent video game company best known for creating the massively popular mobile puzzle game Candy Crush Saga.
  • E. King chosen
    King is a regal title traditionally denoting a male sovereign ruler of a kingdom, often associated with supreme authority and hereditary monarchy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52ad36748190b791de458f2116b2 completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd67a90f308190ab4f912cd1e2f692 completed March 20, 2026, 3:28 p.m.
Created at: March 20, 2026, 12:59 p.m.