Triple

T35585380
Position Surface form Disambiguated ID Type / Status
Subject Anmatyerr people E1028338 entity
Predicate haveArtCentre P38611 FINISHED
Object Ti Tree art centres
Ti Tree art centres are community-run Aboriginal art organisations in the Ti Tree region of Australia that support Anmatyerr artists in producing and selling their artwork.
E2147049 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: Ti Tree art centres | Statement: [Anmatyerr people, haveArtCentre, Ti Tree art centres]
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: Ti Tree art centres
Triple: [Anmatyerr people, haveArtCentre, Ti Tree art centres]
Generated description
Ti Tree art centres are community-run Aboriginal art organisations in the Ti Tree region of Australia that support Anmatyerr artists in producing and selling their artwork.

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_69f76e0495a081909beced418558c0b4 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79e8721a88190b93526c13f5a812a completed May 3, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a385bd4cd7881909b677eb3bf0bcb08 completed June 21, 2026, 9:47 p.m.
NEDg Description generation batch_6a385ca70cc08190abfd88ab51828c9f completed June 21, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a385d704a348190ba1e2de0a90f11f7 completed June 21, 2026, 9:53 p.m.
Created at: May 3, 2026, 4:04 p.m.