Triple

T8976897
Position Surface form Disambiguated ID Type / Status
Subject Mt Eden Avenue E214413 entity
Predicate neighborhoodServed P82 FINISHED
Object Mount Eden E101011 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: Mount Eden | Statement: [Mt Eden Avenue, neighborhoodServed, Mount Eden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Eden
Context triple: [Mt Eden Avenue, neighborhoodServed, Mount Eden]
  • A. Mount Eden chosen
    Mount Eden is a prominent volcanic cone and residential suburb in Auckland, New Zealand, known for its panoramic city views and cultural significance.
  • B. Mount Albert
    Mount Albert is a small rural community in the town of East Gwillimbury, Ontario, known for its village character and surrounding farmland.
  • C. Mount Albert
    Mount Albert is a parliamentary electorate in Auckland, New Zealand, known for being represented by prominent Labour Party leaders including former Prime Minister Jacinda Ardern.
  • D. Mount Albert
    Mount Albert is a volcanic peak and residential suburb in Auckland, New Zealand, known for its prominent scoria cone and surrounding urban community.
  • E. Tama Hills
    Tama Hills is a hilly, wooded area in western Tokyo and Kanagawa Prefecture known for its parks, residential neighborhoods, and natural landscapes on the outskirts of the Tokyo metropolitan region.
  • 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_69ca839ea8b88190922c6a326ffcc0d3 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6786c880819088393bb107a7364c completed April 1, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc96aa46c81908b95a23fd2b4da57 completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:02 p.m.