Triple

T4937147
Position Surface form Disambiguated ID Type / Status
Subject University of Genoa E110839 entity
Predicate hasCampus P116 FINISHED
Object Savona E320914 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: Savona | Statement: [University of Genoa, hasCampus, Savona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Savona
Context triple: [University of Genoa, hasCampus, Savona]
  • A. Savona chosen
    Savona is a coastal city and port in the Liguria region of northwestern Italy, known historically as a strategic maritime center on the Italian Riviera.
  • B. Ventimiglia
    Ventimiglia is a coastal town in northwestern Italy’s Liguria region, known as a key gateway between Italy and France and for its historic center and Mediterranean beaches.
  • C. La Spezia
    La Spezia is a port city in northwestern Italy known as a major naval base and gateway to the Cinque Terre on the Ligurian coast.
  • D. San Remigio
    San Remigio is a coastal municipality in the province of Cebu in the Philippines, known for its long stretch of white-sand beaches and dive spots.
  • E. Bordighera
    Bordighera is a coastal town on the Italian Riviera in Liguria, known for its mild climate, palm-lined seafront, and historic appeal as a 19th-century resort.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7085b1dc819099408f6503f0210f completed March 20, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef7e68058819089e179a29ab700bc completed March 21, 2026, 7:56 p.m.
Created at: March 20, 2026, 1:31 p.m.