Triple

T10004448
Position Surface form Disambiguated ID Type / Status
Subject Elsa Hosk E198207 entity
Predicate name P16 FINISHED
Object Elsa Hosk E198207 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: Elsa Hosk | Statement: [Elsa Hosk, name, Elsa Hosk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elsa Hosk
Context triple: [Elsa Hosk, name, Elsa Hosk]
  • A. Elsa Hosk chosen
    Elsa Hosk is a Swedish fashion model best known for her work with Victoria’s Secret, including serving as one of its prominent Angels and walking in numerous high-profile runway shows.
  • B. Helena Christensen
    Helena Christensen is a Danish supermodel and photographer who rose to international fame in the 1990s, notably as a Victoria’s Secret Angel and a prominent fashion campaign star.
  • C. Suki Waterhouse
    Suki Waterhouse is an English model, actress, and singer known for her fashion work, film roles, and music career.
  • D. Vanessa Pike
    Vanessa Pike is an actress known for her role in the 1995 horror film "The Mangler," adapted from a Stephen King short story.
  • E. Natassia Malthe
    Natassia Malthe is a Norwegian-Canadian actress and model known for her roles in action and fantasy films and television series.
  • 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_69ca830fcca48190bbbd9b20c233835f completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd141ec08190b857fe7e15a8df93 completed April 2, 2026, 1:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a5058a08190b850d30ca0ee8bc8 completed April 5, 2026, 1:57 p.m.
Created at: March 30, 2026, 8:51 p.m.