Triple

T14053766
Position Surface form Disambiguated ID Type / Status
Subject William Charles Henry Friso E338158 entity
Predicate givenName P17 FINISHED
Object Henry E254557 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: Henry | Statement: [William Charles Henry Friso, givenName, Henry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henry
Context triple: [William Charles Henry Friso, givenName, Henry]
  • A. Henry
    Henry is the central protagonist of the video game "Gray Matter," around whom the story’s mystery and events revolve.
  • B. Henry
    Henry is the disturbed serial killer protagonist of the cult horror film "Henry: Portrait of a Serial Killer," portrayed by Michael Rooker.
  • C. Henry
    Henry is the given name of Henry A. Kissinger, the influential American diplomat and political scientist who served as U.S. Secretary of State and National Security Advisor.
  • D. Henry
    Henry is the given first name of Hank Steinbrenner, a late co-owner and general partner of the New York Yankees baseball team.
  • E. Henry chosen
    Henry is a masculine given name of Germanic origin that has been widely used by European royalty and notable historical figures.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8bc54c8190a12f0fc056568538 completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd09b7d148190ad9a146121be01f8 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:20 p.m.