Triple

T12231642
Position Surface form Disambiguated ID Type / Status
Subject Moon Knight E291489 entity
Predicate alterEgo P39 FINISHED
Object Steven Grant E374393 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: Steven Grant | Statement: [Moon Knight, alterEgo, Steven Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steven Grant
Context triple: [Moon Knight, alterEgo, Steven Grant]
  • A. Steven Grant chosen
    Steven Grant is one of the main identities of the Marvel Comics character Moon Knight, portrayed in the Marvel Cinematic Universe by Oscar Isaac.
  • B. Arthur Grant
    Arthur Grant was a British cinematographer best known for his work on numerous Hammer Films productions in the mid-20th century.
  • C. Michael Graydon
    Michael Graydon is a retired senior Royal Air Force officer who served as a leading commander of British fighter aviation during the late 20th century.
  • D. Jonathan Scott
    Jonathan Scott is a wildlife photographer and television presenter best known for his work on BBC nature documentaries, particularly those focusing on big cats in Africa.
  • E. Jonathan Scott
    Jonathan Scott is a Canadian television personality and licensed contractor best known as one half of the twin duo on the home renovation series "Property Brothers."
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca45bd48190b8b7f6b29b6bb25b completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60aad2d488190ba36588e3376ca1a completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:51 p.m.