Triple

T20038577
Position Surface form Disambiguated ID Type / Status
Subject Horowhenua District E497347 entity
Predicate containsSettlement P847 FINISHED
Object Opiki NE NERFINISHED

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: Opiki | Statement: [Horowhenua District, containsSettlement, Opiki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Opiki
Context triple: [Horowhenua District, containsSettlement, Opiki]
  • A. Opiki chosen
    Opiki is a small rural settlement in New Zealand’s Manawatū region, known for its farming community and proximity to the Manawatū River.
  • B. Opoji
    Opoji is a town and traditional community within the Esan ethnic area of Edo State, Nigeria, known for its indigenous customs and local governance structures.
  • C. Pipiriki
    Pipiriki is a small rural settlement in New Zealand’s central North Island, known as a gateway to the Whanganui River and Whanganui National Park.
  • D. Piopio
    Piopio is a small rural township in New Zealand’s King Country region, known for its farming community and scenic surroundings.
  • E. Pipikoro
    Pipikoro is an Austronesian language spoken in Central Sulawesi, Indonesia, known locally as an alternate name for the Uma language.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da627278c88190babe4297a9df1236 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662e9e99c81909b7d50eac893c414 completed April 20, 2026, 5:31 p.m.
Created at: April 11, 2026, 3:36 p.m.