Triple

T24170038
Position Surface form Disambiguated ID Type / Status
Subject Lin Onus E599100 entity
Predicate hasWork P6260 FINISHED
Object Fish and Storm Clouds
"Fish and Storm Clouds" is a notable painting by Australian Aboriginal artist Lin Onus that blends photorealism and Indigenous symbolism to explore themes of culture, landscape, and identity.
E1621040 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: Fish and Storm Clouds | Statement: [Lin Onus, hasWork, Fish and Storm Clouds]
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: Fish and Storm Clouds
Triple: [Lin Onus, hasWork, Fish and Storm Clouds]
Generated description
"Fish and Storm Clouds" is a notable painting by Australian Aboriginal artist Lin Onus that blends photorealism and Indigenous symbolism to explore themes of culture, landscape, and identity.

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_69e288cbd62881909de32ca64a70c17b completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e179322c8190a78166c07a3ef765 completed April 29, 2026, 10:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad3b83c88190b1559dc55506d3b9 completed May 22, 2026, 1:11 a.m.
NEDg Description generation batch_6a0fae8985d881908eb5156cd9653b4a completed May 22, 2026, 1:16 a.m.
NED2 Entity disambiguation (via description) batch_6a0faf345eac8190b8a648c3add470bd completed May 22, 2026, 1:19 a.m.
Created at: April 17, 2026, 11:33 p.m.