Triple

T24139671
Position Surface form Disambiguated ID Type / Status
Subject Waitaki E598191 entity
Predicate recreatedFrom P28666 FINISHED
Object Rakaia electorate
The Rakaia electorate was a former New Zealand parliamentary constituency centered on the rural Canterbury region, represented in the House of Representatives at various periods in the late 19th and 20th centuries.
E1631855 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: Rakaia electorate | Statement: [Waitaki, recreatedFrom, Rakaia electorate]
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: Rakaia electorate
Triple: [Waitaki, recreatedFrom, Rakaia electorate]
Generated description
The Rakaia electorate was a former New Zealand parliamentary constituency centered on the rural Canterbury region, represented in the House of Representatives at various periods in the late 19th and 20th centuries.

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_69e288c92e448190ac57034fa0c863ce completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e004fd38819080135a069e98a3e1 completed April 29, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd63b470c8190afae53fee4f28c7e completed May 22, 2026, 4:06 a.m.
NEDg Description generation batch_6a0fd785e66c8190971031df082764bf completed May 22, 2026, 4:11 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd83e09ac81909c039cdcf5e2d022 completed May 22, 2026, 4:14 a.m.
Created at: April 17, 2026, 11:28 p.m.