Triple

T4622233
Position Surface form Disambiguated ID Type / Status
Subject Eden Park E101011 entity
Predicate locatedIn P40 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: [Eden Park, locatedIn, Mount Eden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Eden
Context triple: [Eden Park, locatedIn, 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 parliamentary electorate in Auckland, New Zealand, known for being represented by prominent Labour Party leaders including former Prime Minister Jacinda Ardern.
  • C. 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.
  • D. Mount Victoria, Wellington
    Mount Victoria, Wellington is a prominent hill and residential suburb near central Wellington, New Zealand, known for its panoramic city and harbor views and popular walking tracks.
  • E. Nakasero Hill
    Nakasero Hill is an upscale, central neighborhood in Kampala known for hosting government offices, embassies, luxury hotels, and commercial centers.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a0374308190aeaffc9d866a3742 completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69be035d661c8190b4ef7d4531170f73 completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:12 p.m.