Triple

T21702671
Position Surface form Disambiguated ID Type / Status
Subject Rodney District E535695 entity
Predicate containsRiver P165 FINISHED
Object Kaukapakapa River
The Kaukapakapa River is a waterway in the Auckland Region of New Zealand’s North Island, flowing through rural landscapes before joining the Kaipara Harbour.
E1785237 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: Kaukapakapa River | Statement: [Rodney District, containsRiver, Kaukapakapa River]
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: Kaukapakapa River
Triple: [Rodney District, containsRiver, Kaukapakapa River]
Generated description
The Kaukapakapa River is a waterway in the Auckland Region of New Zealand’s North Island, flowing through rural landscapes before joining the Kaipara Harbour.

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_69e0c46b44c0819088ab883ebd44e0e8 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef9b8161348190842c433531cfaa5b completed April 27, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e4247c6c81909e8cc1c969a80779 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e4da65dc8190801cafed5fb95685 completed May 24, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5acc5c8819081be9900ea407d65 completed May 24, 2026, 11:49 a.m.
Created at: April 16, 2026, 6:45 p.m.