Triple

T419299
Position Surface form Disambiguated ID Type / Status
Subject Predappio E8064 entity
Predicate hasSubdivision P747 FINISHED
Object San Savino
San Savino is a small locality within the municipality of Predappio in the Emilia-Romagna region of northern Italy.
E77290 NE FINISHED

How this triple was built (4 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: San Savino | Statement: [Predappio, hasSubdivision, San Savino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Savino
Context triple: [Predappio, hasSubdivision, San Savino]
  • A. Rimini
    Rimini is a historic Italian coastal city on the Adriatic Sea, renowned for its beaches, Roman and Renaissance landmarks, and vibrant tourism industry.
  • B. Grignano
    Grignano is a coastal locality near Trieste in northeastern Italy, known for its scenic bay and proximity to Miramare Castle.
  • C. Livorno
    Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
  • D. Pitigliano
    Pitigliano is a picturesque hilltop town in southern Tuscany, Italy, renowned for its well-preserved Jewish heritage and historic ghetto, earning it the nickname “Little Jerusalem.”
  • E. Pescara
    Pescara is a coastal city in the Abruzzo region of central Italy, known for its Adriatic beaches, modern urban layout, and role as a commercial and tourist hub.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: San Savino
Triple: [Predappio, hasSubdivision, San Savino]
Generated description
San Savino is a small locality within the municipality of Predappio in the Emilia-Romagna region of northern Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: San Savino
Target entity description: San Savino is a small locality within the municipality of Predappio in the Emilia-Romagna region of northern Italy.
  • A. Rimini
    Rimini is a historic Italian coastal city on the Adriatic Sea, renowned for its beaches, Roman and Renaissance landmarks, and vibrant tourism industry.
  • B. Grignano
    Grignano is a coastal locality near Trieste in northeastern Italy, known for its scenic bay and proximity to Miramare Castle.
  • C. Livorno
    Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
  • D. Pitigliano
    Pitigliano is a picturesque hilltop town in southern Tuscany, Italy, renowned for its well-preserved Jewish heritage and historic ghetto, earning it the nickname “Little Jerusalem.”
  • E. Pescara
    Pescara is a coastal city in the Abruzzo region of central Italy, known for its Adriatic beaches, modern urban layout, and role as a commercial and tourist hub.
  • F. None of above. chosen

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_69a2e7f1d1bc81909cf2dc9754a3c334 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ee917de48190965fba455efd2320 completed Feb. 28, 2026, 1:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69a55a7165988190bc4312ca40770e27 completed March 2, 2026, 9:37 a.m.
NEDg Description generation batch_69a55ad98dc881909f0e78acee4c6ac2 completed March 2, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_69a55baf54bc81909366f20361a8c387 completed March 2, 2026, 9:43 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.