Triple

T36809080
Position Surface form Disambiguated ID Type / Status
Subject Tweed Regional Museum Murwillumbah E909537 entity
Predicate partOf P40 FINISHED
Object Tweed Regional Museum
Tweed Regional Museum is a regional cultural institution in the Tweed Shire of New South Wales that preserves and showcases the area’s social, natural, and Indigenous history across multiple sites.
E2198394 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: Tweed Regional Museum | Statement: [Tweed Regional Museum Murwillumbah, partOf, Tweed Regional Museum]
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: Tweed Regional Museum
Triple: [Tweed Regional Museum Murwillumbah, partOf, Tweed Regional Museum]
Generated description
Tweed Regional Museum is a regional cultural institution in the Tweed Shire of New South Wales that preserves and showcases the area’s social, natural, and Indigenous history across multiple sites.

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_69f76e7cbbf48190891227b14d041139 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7ca6c63c881909261bd40ba6b414b completed May 3, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3d17b65f448190af10d2786fea23f6 completed June 25, 2026, 11:57 a.m.
NEDg Description generation batch_6a3d19aed8d88190aad7cf2a9fa8df16 completed June 25, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a3d2c4c5d0881908569853ba7876029 completed June 25, 2026, 1:25 p.m.
Created at: May 3, 2026, 4:13 p.m.