Triple

T11243164
Position Surface form Disambiguated ID Type / Status
Subject The Cameraman E266125 entity
Predicate screenwriter P2831 FINISHED
Object John Grey E694524 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: John Grey | Statement: [The Cameraman, screenwriter, John Grey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Grey
Context triple: [The Cameraman, screenwriter, John Grey]
  • A. John Grey
    John Grey is a central character in Anthony Trollope’s novel "Can You Forgive Her?", portrayed as a principled, reserved country gentleman whose steadfast love and moral integrity contrast with the heroine’s indecision.
  • B. John Grey chosen
    John Grey is a writer best known for his work on the film "The Freshman."
  • C. Martin Black
    Martin Black is a member of the Black family, a fictional pure-blood wizarding family in the Harry Potter universe.
  • D. John Keen
    John Keen is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Keen.
  • E. Dick Logan
    Dick Logan was a prominent figure associated with aviation or local leadership in Billings, Montana, for whom Billings Logan International Airport is named.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e91b0b808190bc38008bb344d180 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad849f70819098a7056fbc4831ff completed April 19, 2026, 10:25 a.m.
Created at: April 8, 2026, 9:30 p.m.