Triple

T29053291
Position Surface form Disambiguated ID Type / Status
Subject Inspector-General of Intelligence and Security (New Zealand) E735321 entity
Predicate hasOfficeHolder P537 FINISHED
Object Cheryl Gwyn
Cheryl Gwyn is a New Zealand lawyer and public servant who has served as the country's Inspector-General of Intelligence and Security, overseeing the legality and propriety of its intelligence agencies.
E1868133 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: Cheryl Gwyn | Statement: [Inspector-General of Intelligence and Security (New Zealand), hasOfficeHolder, Cheryl Gwyn]
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: Cheryl Gwyn
Triple: [Inspector-General of Intelligence and Security (New Zealand), hasOfficeHolder, Cheryl Gwyn]
Generated description
Cheryl Gwyn is a New Zealand lawyer and public servant who has served as the country's Inspector-General of Intelligence and Security, overseeing the legality and propriety of its intelligence agencies.

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_69f077e64b88819094d37bdbca8191b3 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f66067f58c819087237fa88ad513cb completed May 2, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0ebe2808190a7fd4b22b2fe5184 completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f4da9f7c819083246705f4e1986c completed June 7, 2026, 10:46 p.m.
NED2 Entity disambiguation (via description) batch_6a25f52aa8288190b362a0cceceb49c3 completed June 7, 2026, 10:48 p.m.
Created at: April 28, 2026, 10:09 a.m.