Triple

T12262426
Position Surface form Disambiguated ID Type / Status
Subject UTS E292256 entity
Predicate locatedIn P40 FINISHED
Object Ultimo, Sydney E867400 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: Ultimo, Sydney | Statement: [UTS, locatedIn, Ultimo, Sydney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ultimo, Sydney
Context triple: [UTS, locatedIn, Ultimo, Sydney]
  • A. Ultimo, Sydney chosen
    Ultimo is an inner-city suburb of Sydney, Australia, known for its educational institutions, cultural venues, and proximity to the central business district.
  • B. Nadi–Sydney
    Nadi–Sydney is an international flight route linking Nadi, Fiji with Sydney, Australia, serving as a key connection between the South Pacific and one of Australia’s major cities.
  • C. Sydney
    Sydney is a recurring character in Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," known for her sharp intellect and complex personal relationships within its ensemble cast.
  • D. Sydney
    Sydney is Australia's largest and most populous city, renowned for its iconic harbour, Opera House, and Harbour Bridge.
  • E. Sydney
    Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cdb0a948190aeee4ca3c01f801e completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60ac3ce008190856a917c2c75862a completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:52 p.m.