Triple

T14123632
Position Surface form Disambiguated ID Type / Status
Subject Lady Amelia Windsor E339965 entity
Predicate representedBy P1748 FINISHED
Object Storm Model Management E835851 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: Storm Model Management | Statement: [Lady Amelia Windsor, representedBy, Storm Model Management]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Storm Model Management
Context triple: [Lady Amelia Windsor, representedBy, Storm Model Management]
  • A. Storm Model Management chosen
    Storm Model Management is a prominent London-based modeling agency known for discovering and representing high-profile fashion models.
  • B. Storm Center
    Storm Center is a 1956 American drama film about censorship and anti-communist hysteria, notable for starring Bette Davis as a small-town librarian who refuses to remove a controversial book.
  • C. Storm
    "Storm" is a track by Blue Electric Light, likely featuring an energetic, electrified sound that reflects the band's style.
  • D. Storm
    Storm is a common surname shared by various real and fictional individuals, notably including members of the superhero team the Fantastic Four.
  • E. Storm
    Storm is the short name of the Lake Elsinore Storm, a Minor League Baseball team based in Lake Elsinore, California.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6095548881908a9e66adccca92d2 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf0a7a7c8190860d8ce47b5f0732 completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:22 p.m.