Triple

T33289511
Position Surface form Disambiguated ID Type / Status
Subject Penistone E852275 entity
Predicate hasSecondarySchool P3445 FINISHED
Object Penistone Grammar School
Penistone Grammar School is a long-established secondary school and sixth form serving the town of Penistone and surrounding areas in South Yorkshire, England.
E2044068 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: Penistone Grammar School | Statement: [Penistone, hasSecondarySchool, Penistone Grammar School]
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: Penistone Grammar School
Triple: [Penistone, hasSecondarySchool, Penistone Grammar School]
Generated description
Penistone Grammar School is a long-established secondary school and sixth form serving the town of Penistone and surrounding areas in South Yorkshire, England.

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_69f349660ff48190a4568803d0b89941 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6de76e05881908a6eee3fc1f10c9f completed May 3, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35392bca308190a2a262b52d1ddc1d completed June 19, 2026, 12:42 p.m.
NEDg Description generation batch_6a3539e9011c81909b6971dee88beef4 completed June 19, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_6a353aef184481908315142c5ef2004a completed June 19, 2026, 12:49 p.m.
Created at: May 1, 2026, 1:32 a.m.