Triple

T35857167
Position Surface form Disambiguated ID Type / Status
Subject Bruno Munari E1036540 entity
Predicate notableWork P4 FINISHED
Object Design as Art
Design as Art is a seminal book by Italian designer Bruno Munari that explores the fusion of everyday design and artistic expression, arguing that good design should be both functional and aesthetically enriching.
E2158747 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: Design as Art | Statement: [Bruno Munari, notableWork, Design as Art]
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: Design as Art
Triple: [Bruno Munari, notableWork, Design as Art]
Generated description
Design as Art is a seminal book by Italian designer Bruno Munari that explores the fusion of everyday design and artistic expression, arguing that good design should be both functional and aesthetically enriching.

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_69f76e1b4aa481909630373171eb5ec6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a97293a0819084fe659c3ad53fbd completed May 3, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_6a389c32af3c819092b552f97f15a3f1 completed June 22, 2026, 2:21 a.m.
NEDg Description generation batch_6a389eec81f08190992f2f09e4978523 completed June 22, 2026, 2:33 a.m.
NED2 Entity disambiguation (via description) batch_6a389f77f7508190b12cc2abde3383b4 completed June 22, 2026, 2:35 a.m.
Created at: May 3, 2026, 4:06 p.m.