Triple

T5237568
Position Surface form Disambiguated ID Type / Status
Subject Department of Transport and Planning (Victoria) E118259 entity
Predicate headquartersLocation P62 FINISHED
Object Melbourne 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 | Statement: [Department of Transport and Planning (Victoria), headquartersLocation, Melbourne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melbourne
Context triple: [Department of Transport and Planning (Victoria), headquartersLocation, Melbourne]
  • A. Melbourne
    Melbourne is a historic market town in Derbyshire, England, known for its Georgian architecture and the notable Melbourne Hall and gardens.
  • B. 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.
  • C. Melbourn
    Melbourn is a village and civil parish in South Cambridgeshire, England, known for its historic architecture and rural community character.
  • 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_69bd4467db0881909b3b0982df32cc8f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b27990c8190b6a3c24de09c8c18 completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe51fe988190afcba16381b33043 completed March 21, 2026, 8:23 p.m.
Created at: March 20, 2026, 1:49 p.m.