Triple

T36542277
Position Surface form Disambiguated ID Type / Status
Subject New Zealand District Health Boards E901052 entity
Predicate hadUnit P1198 FINISHED
Object Southern District Health Board
Southern District Health Board was the publicly funded organization responsible for providing and funding health services in New Zealand’s southernmost regions, including Otago and Southland.
E2191322 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: Southern District Health Board | Statement: [New Zealand District Health Boards, hadUnit, Southern District Health Board]
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: Southern District Health Board
Triple: [New Zealand District Health Boards, hadUnit, Southern District Health Board]
Generated description
Southern District Health Board was the publicly funded organization responsible for providing and funding health services in New Zealand’s southernmost regions, including Otago and Southland.

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_69f76e61217081908b79d610fe67b013 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c242cb5c81909b711a7d1296d54f completed May 3, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39f9042a4c81909c407d5ae4811f43 completed June 23, 2026, 3:09 a.m.
NEDg Description generation batch_6a39fd1507bc819095303e719a6e33ca completed June 23, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_6a39fd67f4808190aab9e0d94bb5e328 completed June 23, 2026, 3:28 a.m.
Created at: May 3, 2026, 4:11 p.m.