Triple

T32686574
Position Surface form Disambiguated ID Type / Status
Subject Redbank Plains E835742 entity
Predicate hasShoppingCentre P4285 FINISHED
Object Town Square Redbank Plains
Town Square Redbank Plains is a major suburban shopping centre in Redbank Plains, Queensland, featuring a range of retail stores, supermarkets, dining options, and community services.
 E2017367 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: Town Square Redbank Plains | Statement: [Redbank Plains, hasShoppingCentre, Town Square Redbank Plains]
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: Town Square Redbank Plains
Triple: [Redbank Plains, hasShoppingCentre, Town Square Redbank Plains]
Generated description
Town Square Redbank Plains is a major suburban shopping centre in Redbank Plains, Queensland, featuring a range of retail stores, supermarkets, dining options, and community services.

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_69f3493211388190993801216afbc2a7 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c81665688190bc0cde92cf4d619f completed May 3, 2026, 3:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3492c808408190aef3b10fa4065194 completed June 19, 2026, 12:52 a.m.
NEDg Description generation batch_6a3493bc839c8190ade6ca8ccf125853 completed June 19, 2026, 12:56 a.m.
NED2 Entity disambiguation (via description) batch_6a34948e92348190bec1eb58502e919f completed June 19, 2026, 12:59 a.m.
Created at: May 1, 2026, 1:09 a.m.