Triple

T10785103
Position Surface form Disambiguated ID Type / Status
Subject Lord Mayor of Melbourne E254431 entity
Predicate positionHeldIn P8 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: [Lord Mayor of Melbourne, positionHeldIn, Melbourne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melbourne
Context triple: [Lord Mayor of Melbourne, positionHeldIn, Melbourne]
  • 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. Melbourne
    Melbourne is a historic market town in Derbyshire, England, known for its Georgian architecture and the notable Melbourne Hall and gardens.
  • C. Melbourne
    Melbourne is a coastal city in east-central Florida known for its beaches, aerospace and technology industries, and role as a commercial and cultural hub of the Space Coast.
  • D. Melbourn
    Melbourn is a village and civil parish in South Cambridgeshire, England, known for its historic architecture and rural community character.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732d2e7cc8190a4cb9a4d7c76ab15 completed April 9, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3e6d27d8c8190b2c8ee9c54cf7fd1 completed April 18, 2026, 8:17 p.m.
Created at: April 8, 2026, 9:17 p.m.