Triple

T36447468
Position Surface form Disambiguated ID Type / Status
Subject Ngāti Raukawa ki te Tonga E897915 entity
Predicate hasHapū P96966 FINISHED
Object Ngāti Rākau
Ngāti Rākau is a hapū (sub-tribe) of the wider Ngāti Raukawa ki te Tonga iwi in Aotearoa New Zealand.
E2196338 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: Ngāti Rākau | Statement: [Ngāti Raukawa ki te Tonga, hasHapū, Ngāti Rākau]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ngāti Rākau
Triple: [Ngāti Raukawa ki te Tonga, hasHapū, Ngāti Rākau]
Generated description
Ngāti Rākau is a hapū (sub-tribe) of the wider Ngāti Raukawa ki te Tonga iwi in Aotearoa New Zealand.

Provenance (5 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_69f76e5720b481908f8177ac24a7560b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd8d695081908786791a5b4f4dcc completed May 3, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a3809354881909427c06e4fb9256b completed June 23, 2026, 7:38 a.m.
NEDg Description generation batch_6a3a39e3d4b88190b32358716af6437d completed June 23, 2026, 7:46 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3ec37358819082773664f65f058b completed June 23, 2026, 8:07 a.m.
Created at: May 3, 2026, 4:10 p.m.