Triple

T4810153
Position Surface form Disambiguated ID Type / Status
Subject Peter C. Doherty E107049 entity
Predicate placeOfBirth P1 FINISHED
Object Brisbane E14172 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: Brisbane | Statement: [Peter C. Doherty, placeOfBirth, Brisbane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brisbane
Context triple: [Peter C. Doherty, placeOfBirth, Brisbane]
  • A. Brisbane chosen
    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.
  • B. Brisbane
    Brisbane is a small city in northern San Mateo County, California, located just south of San Francisco on the lower slopes of San Bruno Mountain.
  • C. Melbourne
    Melbourne is a historic market town in Derbyshire, England, known for its Georgian architecture and the notable Melbourne Hall and gardens.
  • D. Melbourne
    Melbourne is a major Australian city known for its vibrant arts scene, diverse culture, and status as a leading center for sports and education.
  • 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_69bd43f779448190b92885cb70abb6c2 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c7b879081908e0c92a67422906e completed March 20, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5ca8c29081909701bfd4ea60586d completed March 21, 2026, 8:54 a.m.
Created at: March 20, 2026, 1:23 p.m.