Triple

T38301253
Position Surface form Disambiguated ID Type / Status
Subject Wardandi people E1032225 entity
Predicate hasOngoingConnectionTo P8776 FINISHED
Object Busselton–Margaret River region
The Busselton–Margaret River region is a coastal area in Western Australia renowned for its wineries, surf beaches, and natural beauty.
 E324238 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: Busselton–Margaret River region | Statement: [Wardandi people, hasOngoingConnectionTo, Busselton–Margaret River region]
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: Busselton–Margaret River region
Triple: [Wardandi people, hasOngoingConnectionTo, Busselton–Margaret River region]
Generated description
The Busselton–Margaret River region is a coastal area in Western Australia renowned for its wineries, surf beaches, and natural beauty.

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_69f76e0f2084819091299d021625c3fe completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc619dbd48190919184b2f50e2cf7 completed May 7, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41c272aab4819096df3bc3fcd39c2f completed June 29, 2026, 12:55 a.m.
NEDg Description generation batch_6a41c2ea3c6c81909fe5e580e06e7db8 completed June 29, 2026, 12:57 a.m.
NED2 Entity disambiguation (via description) batch_6a41c37df8ec8190bd19801d63bb28e9 completed June 29, 2026, 12:59 a.m.
Created at: May 3, 2026, 4:30 p.m.