Triple

T12777002
Position Surface form Disambiguated ID Type / Status
Subject Anchor Island E305402 entity
Predicate hasFauna P950 FINISHED
Object takahē E447032 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: takahē | Statement: [Anchor Island, hasFauna, takahē]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: takahē
Context triple: [Anchor Island, hasFauna, takahē]
  • A. takahē chosen
    The takahē is a large, flightless, and once-thought-extinct New Zealand rail known for its vivid blue-green plumage and conservation success story.
  • B. Matakohe
    Matakohe is a small rural settlement in New Zealand best known for its Kauri Museum and historic connections to the kauri gum and timber industries.
  • C. Rakahanga
    Rakahanga is a remote coral atoll in the northern Cook Islands known for its traditional Polynesian culture and small, close-knit community.
  • D. Rakaia
    Rakaia is a small rural town in Canterbury, New Zealand, known for its proximity to the Rakaia River and its strong agricultural and fishing activities.
  • E. Ruakākā
    Ruakākā is a small coastal town in New Zealand known for its long sandy beach, surf breaks, and proximity to the Marsden Point industrial area.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e595e008190b42dff3012d17d66 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f685013e0481908db09302a2ced207 completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:29 p.m.