Triple

T511598
Position Surface form Disambiguated ID Type / Status
Subject Princeton University Press E10620 entity
Predicate hasOfficeIn P1268 FINISHED
Object Melbourne, Australia E4488 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: Melbourne, Australia | Statement: [Princeton University Press, hasOfficeIn, Melbourne, Australia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melbourne, Australia
Context triple: [Princeton University Press, hasOfficeIn, Melbourne, Australia]
  • A. Melbourne chosen
    Melbourne is a major Australian city known for its vibrant arts scene, diverse culture, and status as a leading center for sports and education.
  • B. Sydney
    Sydney is Australia's largest and most populous city, renowned for its iconic harbour, Opera House, and Harbour Bridge.
  • C. Brisbane
    Brisbane is the capital and most populous city of the Australian state of Queensland, known for its subtropical climate, riverfront setting, and role as a major economic and cultural hub.
  • D. Wollongong
    Wollongong is a coastal city in Australia known for its heavy industry, port facilities, and popular surf beaches along the Illawarra region.
  • E. Adelaide
    Adelaide is the coastal capital city of South Australia, known for its festivals, wine regions, and planned grid layout.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f16768c081909d05537ff070868b completed Feb. 28, 2026, 1:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b5d3b5f0819093c5d55bdf5a7c4d completed March 1, 2026, 9:55 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.