Triple

T10505402
Position Surface form Disambiguated ID Type / Status
Subject Kensington, Sydney E247772 entity
Predicate hasNeighbour P5707 FINISHED
Object Moore Park E141499 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: Moore Park | Statement: [Kensington, Sydney, hasNeighbour, Moore Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moore Park
Context triple: [Kensington, Sydney, hasNeighbour, Moore Park]
  • A. Moore Park chosen
    Moore Park is an inner-city suburb and major sporting and entertainment precinct in Sydney, New South Wales, Australia.
  • B. Howard Park
    Howard Park is a prominent public park and recreational area in South Bend, Indiana, known for its riverfront setting and community amenities.
  • C. Sansom Park
    Sansom Park is a small city located in Tarrant County, Texas, within the Dallas–Fort Worth metropolitan area.
  • D. Gladstone Park
    Gladstone Park is a large public park in northwest London known for its open green spaces, sports facilities, and panoramic views over the city.
  • E. Gladstone Park
    Gladstone Park is a residential suburb in Melbourne, Victoria, known for its proximity to Tullamarine Airport and family-oriented community amenities.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509a07c908190bf0e3e5d480b306d completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5561714a081909cbf1cc7d5d0ac0a completed April 19, 2026, 10:24 p.m.
Created at: April 6, 2026, 12:26 p.m.