Triple

T36584399
Position Surface form Disambiguated ID Type / Status
Subject Māori Representation Act 1867 E902482 entity
Predicate createdElectorate P42151 FINISHED
Object Eastern Māori
Eastern Māori was a former New Zealand parliamentary Māori electorate that represented Māori communities in the eastern regions of the North Island.
E2193550 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: Eastern Māori | Statement: [Māori Representation Act 1867, createdElectorate, Eastern Māori]
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: Eastern Māori
Triple: [Māori Representation Act 1867, createdElectorate, Eastern Māori]
Generated description
Eastern Māori was a former New Zealand parliamentary Māori electorate that represented Māori communities in the eastern regions of the North Island.

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_69f76e64d8908190868473959a250b94 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69ffaac11d7c819088c2081b4d8f2b54 completed May 9, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20b90f688190bc49703a1d453cd3 completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a240b0fb88190b28f44738c33ee21 completed June 23, 2026, 6:13 a.m.
NED2 Entity disambiguation (via description) batch_6a3a24730a5481908ede82ed275639f3 completed June 23, 2026, 6:15 a.m.
Created at: May 3, 2026, 4:11 p.m.