Triple

T38681597
Position Surface form Disambiguated ID Type / Status
Subject Works by Raphael E943903 entity
Predicate hasNotableWork P4 FINISHED
Object The Vision of a Knight
The Vision of a Knight is a small early Renaissance panel painting by Raphael depicting a sleeping knight visited by allegorical female figures, often interpreted as a choice between virtue and pleasure.
E2280710 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: The Vision of a Knight | Statement: [Works by Raphael, hasNotableWork, The Vision of a Knight]
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: The Vision of a Knight
Triple: [Works by Raphael, hasNotableWork, The Vision of a Knight]
Generated description
The Vision of a Knight is a small early Renaissance panel painting by Raphael depicting a sleeping knight visited by allegorical female figures, often interpreted as a choice between virtue and pleasure.

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_69f76eec28708190b9c82a505fc278e0 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fcdc3e3abc8190a294a8a877340915 completed May 7, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41fd7735cc81908c892a5afe631354 completed June 29, 2026, 5:07 a.m.
NEDg Description generation batch_6a420030939881908054a086885a8203 completed June 29, 2026, 5:18 a.m.
NED2 Entity disambiguation (via description) batch_6a4200a1bc48819096ef4bdffba352a4 completed June 29, 2026, 5:20 a.m.
Created at: May 3, 2026, 4:33 p.m.