Triple

T14381495
Position Surface form Disambiguated ID Type / Status
Subject Wallangarra E356612 entity
Predicate nearbyTown P3883 FINISHED
Object Tenterfield E73709 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: Tenterfield | Statement: [Wallangarra, nearbyTown, Tenterfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tenterfield
Context triple: [Wallangarra, nearbyTown, Tenterfield]
  • A. Tenterfield chosen
    Tenterfield is a historic rural town in New South Wales, Australia, known for its heritage architecture and role in Australian federation history.
  • B. Dungog
    Dungog is a small rural town in New South Wales, Australia, known for its historic architecture, dairy farming, and proximity to the Barrington Tops National Park.
  • C. Booral
    Booral is a small rural locality in New South Wales, Australia, known for its riverside setting and agricultural surroundings.
  • D. Inverell
    Inverell is a rural town in northern New South Wales, Australia, known for its sapphire mining and agricultural production.
  • E. Mudgee
    Mudgee is a historic town in New South Wales, Australia, renowned for its cool-climate wineries, heritage architecture, and vibrant food and wine tourism.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900bbfb08190a1e56f281a2374c0 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5dc9b908190b1d7583810dc9c41 completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 1:16 a.m.