Triple

T15576993
Position Surface form Disambiguated ID Type / Status
Subject Steven Grant E374393 entity
Predicate fullName P16 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: [Steven Grant, fullName, Steven Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steven Grant
Context triple: [Steven Grant, fullName, 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. Steven Grant
    Steven Grant is an American comic book writer best known for creating the graphic novel that inspired the film "2 Guns."
  • C. Arthur Grant
    Arthur Grant was a British cinematographer best known for his work on numerous Hammer Films productions in the mid-20th century.
  • D. 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.
  • E. Nick Grindé
    Nick Grindé was a screenwriter active during early Hollywood cinema, known for contributing to films such as the 1930 drama "The Divorcee."
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e22c89081909b1ec0cd36a1ef45 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56c3efb48190ad94d9d326c6c2c0 completed May 9, 2026, 3:46 p.m.
Created at: April 10, 2026, 4:11 a.m.