Triple

T12308468
Position Surface form Disambiguated ID Type / Status
Subject Richard Gordon E293414 entity
Predicate name P16 FINISHED
Object Richard Gordon E293414 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: Richard Gordon | Statement: [Richard Gordon, name, Richard Gordon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Gordon
Context triple: [Richard Gordon, name, Richard Gordon]
  • A. Richard Gordon chosen
    Richard Gordon is a character in Ernest Hemingway’s novel and its film adaptation "To Have and Have Not," involved in the story’s tense mix of romance, crime, and political intrigue.
  • B. Robert Lovell
    Robert Lovell is known primarily as the husband of Mary Fricker.
  • C. J. R. Clynes
    J. R. Clynes was a British Labour politician who served as Leader of the Labour Party and held senior government posts in the early 20th century.
  • D. George Michael Low
    George Michael Low was an Austrian-born American aerospace engineer and NASA administrator who played a key leadership role in the Apollo program and later served as president of Rensselaer Polytechnic Institute.
  • E. Robert Wisdom
    Robert Wisdom is an American actor best known for his role as Major Howard "Bunny" Colvin on the television series "The Wire."
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f01ace8819087f245b9216f4dc8 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e8243d48190baf25b2927de6c62 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:53 p.m.