Triple

T4633096
Position Surface form Disambiguated ID Type / Status
Subject Annibale Carracci E101462 entity
Predicate influencedBy P9 FINISHED
Object Correggio E167336 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: Correggio | Statement: [Annibale Carracci, influencedBy, Correggio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Correggio
Context triple: [Annibale Carracci, influencedBy, Correggio]
  • A. Correggio chosen
    Correggio was an Italian Renaissance painter renowned for his innovative use of illusionistic perspective, sensuality, and dynamic compositions that influenced later Baroque art.
  • B. Faenza
    Faenza is a historic city in Italy’s Emilia-Romagna region, renowned for its traditional ceramics and artistic majolica production.
  • C. Cremona
    Cremona is a historic city in northern Italy renowned for its tradition of violin making and its well-preserved medieval architecture.
  • D. San Savino
    San Savino is a small locality within the municipality of Predappio in the Emilia-Romagna region of northern Italy.
  • E. Collevecchio
    Collevecchio is a small historic town in the Lazio region of central Italy, known for its hilltop setting and traditional rural character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a5d0de881909baacc5b991f5b53 completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfac317248190a8886d59d2242acb completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.