Triple

T4448539
Position Surface form Disambiguated ID Type / Status
Subject Lyne E96348 entity
Predicate includesArea P1393 FINISHED
Object Taree E52795 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: Taree | Statement: [Lyne, includesArea, Taree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taree
Context triple: [Lyne, includesArea, Taree]
  • A. Taree chosen
    Taree is a regional town in New South Wales, Australia, situated on the Manning River and serving as a commercial and service hub for the surrounding agricultural and coastal communities.
  • B. Tongaat
    Tongaat is a town in KwaZulu-Natal, South Africa, known for its significant Indian community and sugar industry.
  • C. Tiaro
    Tiaro is a small rural town in Queensland, Australia, situated within the Fraser Coast Region and known for its agricultural surroundings and historic charm.
  • D. Tairua
    Tairua is a small coastal town and popular holiday destination on New Zealand’s Coromandel Peninsula, known for its beaches, fishing, and scenic views of nearby offshore islands.
  • E. Ronga
    Ronga is a Bantu language spoken primarily in southern Mozambique, known for contributing vocabulary and structural features to African varieties of Portuguese.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d45b748190b09b7067fc6279b0 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b62818295481909c0ffa377570effc completed March 15, 2026, 3:31 a.m.
Created at: March 12, 2026, 11:32 p.m.