Triple

T36858292
Position Surface form Disambiguated ID Type / Status
Subject Sérgio de Camargo E910857 entity
Predicate notableWork P4 FINISHED
Object Relief No. 215
Relief No. 215 is a geometric, monochromatic wall sculpture by Brazilian artist Sérgio de Camargo, exemplifying his minimalist exploration of light, shadow, and spatial rhythm through modular relief forms.
 E2203704 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: Relief No. 215 | Statement: [Sérgio de Camargo, notableWork, Relief No. 215]
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: Relief No. 215
Triple: [Sérgio de Camargo, notableWork, Relief No. 215]
Generated description
Relief No. 215 is a geometric, monochromatic wall sculpture by Brazilian artist Sérgio de Camargo, exemplifying his minimalist exploration of light, shadow, and spatial rhythm through modular relief forms.

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_69f76e8033d48190a59274f86f13be48 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cfcdcdc0819082bff038fde237f3 completed May 3, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfadc6bc08190b9031f70b139246f completed June 26, 2026, 4:06 a.m.
NEDg Description generation batch_6a3dfd07722c8190bce1f21b79d1edb9 completed June 26, 2026, 4:16 a.m.
NED2 Entity disambiguation (via description) batch_6a3e0e15710c81908d8ea4fc007197d2 completed June 26, 2026, 5:28 a.m.
Created at: May 3, 2026, 4:13 p.m.