Triple

T32786306
Position Surface form Disambiguated ID Type / Status
Subject Villa Godi E838508 entity
Predicate interiorDecorationBy P8228 FINISHED
Object Gian Antonio Fasolo
Gian Antonio Fasolo was a 16th-century Italian painter of the Venetian school, known for his frescoes and decorative work in villas and churches in the Veneto region.
E2034920 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: Gian Antonio Fasolo | Statement: [Villa Godi, interiorDecorationBy, Gian Antonio Fasolo]
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: Gian Antonio Fasolo
Triple: [Villa Godi, interiorDecorationBy, Gian Antonio Fasolo]
Generated description
Gian Antonio Fasolo was a 16th-century Italian painter of the Venetian school, known for his frescoes and decorative work in villas and churches in the Veneto region.

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_69f3493b83f48190be335cd42465cecf completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cd4f6fa88190bee5b76a463ddb9f completed May 3, 2026, 4:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34e4f3a9388190b5f92e5145622005 completed June 19, 2026, 6:42 a.m.
NEDg Description generation batch_6a34e5e7ca0c8190b09741dfb9c7bdb0 completed June 19, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a34e7032cac81909ef52e16456c9a15 completed June 19, 2026, 6:51 a.m.
Created at: May 1, 2026, 1:14 a.m.