Triple

T8007300
Position Surface form Disambiguated ID Type / Status
Subject Province of Varese E186392 entity
Predicate containsMunicipality P852 FINISHED
Object Luino E475631 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: Luino | Statement: [Province of Varese, containsMunicipality, Luino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luino
Context triple: [Province of Varese, containsMunicipality, Luino]
  • A. Luino chosen
    Luino is a town in northern Italy’s Lombardy region, known for its lakeside setting near the Swiss border and its historic weekly market.
  • B. Cervia
    Cervia is a coastal town and popular seaside resort on the Adriatic Sea in Italy’s Emilia-Romagna region, known for its historic salt pans and beaches.
  • C. Viareggio
    Viareggio is a coastal city in Tuscany, Italy, renowned for its seaside resorts and famous annual Carnival.
  • D. Pesaro
    Pesaro is a coastal city on Italy’s Adriatic Sea, known for its Renaissance architecture, seaside resorts, and as the birthplace of composer Gioachino Rossini.
  • E. Livorno
    Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
  • 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3cf8a6048190970685a83fd2f59d completed March 31, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd6744324c8190875444437d8dcc64 completed April 1, 2026, 6:43 p.m.
Created at: March 30, 2026, 5:18 p.m.