Triple

T6996729
Position Surface form Disambiguated ID Type / Status
Subject Henry Haller E162233 entity
Predicate name P16 FINISHED
Object Henry Haller E162233 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 Haller | Statement: [Henry Haller, name, Henry Haller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henry Haller
Context triple: [Henry Haller, name, Henry Haller]
  • A. Henry Haller chosen
    Henry Haller was a Swiss-born American chef best known for serving as White House Executive Chef for multiple U.S. presidents from the Johnson through the Reagan administrations.
  • B. Hugo Carmody
    Hugo Carmody is a charming, somewhat hapless young gentleman from P. G. Wodehouse’s Blandings Castle stories, often embroiled in romantic entanglements and comic misadventures.
  • C. Mark Weissenstern
    Mark Weissenstern is an electronics industry figure best known as a founder of the semiconductor company Signetics.
  • D. Hendrik Sartov
    Hendrik Sartov was a cinematographer best known for his work on silent-era films, including collaborations with major directors and stars of the 1920s.
  • E. Treves
    Treves was a prominent Italian publishing house known for issuing major literary works in the late 19th and early 20th centuries.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbedafa48190af0d2b47e3a1e17e completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a2465908190b69454f6215365b0 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:32 p.m.