Triple

T16167521
Position Surface form Disambiguated ID Type / Status
Subject Pirongia E392343 entity
Predicate nearbyTown P3883 FINISHED
Object Te Awamutu E297772 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: Te Awamutu | Statement: [Pirongia, nearbyTown, Te Awamutu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Te Awamutu
Context triple: [Pirongia, nearbyTown, Te Awamutu]
  • A. Te Awamutu chosen
    Te Awamutu is a rural service town in New Zealand known for its dairy farming hinterland and location south of Hamilton on the North Island.
  • B. Otahuhu
    Otahuhu is a suburb of Auckland, New Zealand, known for its strong Pacific Islander presence and vibrant Tongan community.
  • C. Opotiki
    Ōpōtiki is a small coastal town in New Zealand’s North Island known as a gateway to the East Coast and for its strong Māori cultural heritage and outdoor recreation.
  • D. Palmerston North
    Palmerston North is a major inland city in New Zealand known for its role as an educational and logistical hub, particularly home to Massey University.
  • E. Tauranga
    Tauranga is a major coastal city and port in the Bay of Plenty region of New Zealand, known for its beaches, harbor, and growing economic and tourism sectors.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21eb4ea9c81908806f9771ae80148 completed April 17, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7bb6aac8190a33607abfe9a32d0 completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:02 a.m.