Triple

T14296279
Position Surface form Disambiguated ID Type / Status
Subject Suki Waterhouse E354446 entity
Predicate modeledFor P2006 FINISHED
Object Burberry E317091 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: Burberry | Statement: [Suki Waterhouse, modeledFor, Burberry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burberry
Context triple: [Suki Waterhouse, modeledFor, Burberry]
  • A. Burberry chosen
    Burberry is a British luxury fashion house renowned for its iconic trench coats, distinctive check pattern, and heritage-inspired apparel and accessories.
  • B. Belstaff
    Belstaff is a British heritage fashion brand renowned for its premium motorcycle-inspired outerwear and rugged luxury apparel.
  • C. Loewe
    Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
  • D. Balmain
    Balmain is a historic inner-west suburb of Sydney, Australia, known for its waterfront location on Sydney Harbour, preserved Victorian architecture, and vibrant pub and café culture.
  • E. Balmain
    Balmain is a French luxury fashion house renowned for its opulent, sharply tailored designs and influential presence on international runways.
  • 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_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de717b35ec81908968994e65737c66 completed April 14, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d246ccc81909e9fe8b4487dcc88 completed May 8, 2026, 1:32 a.m.
Created at: April 10, 2026, 1:11 a.m.