Triple

T32111570
Position Surface form Disambiguated ID Type / Status
Subject Te Rūnanga-Ā-Iwi O Ngāpuhi E820129 entity
Predicate operatesIn P82 FINISHED
Object Te Tai Tokerau region
Te Tai Tokerau region is the northernmost part of New Zealand’s North Island, known for its strong Māori presence, subtropical climate, and significant cultural and historical sites.
E2291542 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 Tai Tokerau region | Statement: [Te Rūnanga-Ā-Iwi O Ngāpuhi, operatesIn, Te Tai Tokerau region]
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: Te Tai Tokerau region
Triple: [Te Rūnanga-Ā-Iwi O Ngāpuhi, operatesIn, Te Tai Tokerau region]
Generated description
Te Tai Tokerau region is the northernmost part of New Zealand’s North Island, known for its strong Māori presence, subtropical climate, and significant cultural and historical sites.

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_69f3490209c881908ec0241476715f15 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b903538481909cffcb6cc1cc0e70 completed May 3, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5c6a0dd9b881908b40a5dc23ef7a1f completed July 19, 2026, 6:09 a.m.
NEDg Description generation batch_6a5c6a8f1034819088269f837038f080 completed July 19, 2026, 6:11 a.m.
NED2 Entity disambiguation (via description) batch_6a5c6ae7080881908c01ae0f3e8f2f56 completed July 19, 2026, 6:12 a.m.
Created at: May 1, 2026, 12:27 a.m.