Triple

T19276236
Position Surface form Disambiguated ID Type / Status
Subject Faetano E482061 entity
Predicate hasBorderWith P224 FINISHED
Object Coriano NE NERFINISHED

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: Coriano | Statement: [Faetano, hasBorderWith, Coriano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coriano
Context triple: [Faetano, hasBorderWith, Coriano]
  • A. Coriano chosen
    Coriano is a municipality in Italy’s Emilia-Romagna region, known for its rural landscapes, historic center, and proximity to the Adriatic coast.
  • B. Seregno
    Seregno is a town in the Lombardy region of northern Italy, known for its industrial activity and proximity to Milan.
  • C. Acquaviva Picena
    Acquaviva Picena is a small historic hilltop town in Italy’s Marche region, known for its medieval fortress and views over the surrounding Piceno countryside.
  • D. Ostiano
    Ostiano is a small town in the Lombardy region of northern Italy, known as the birthplace of the Baroque painter Bartolomeo Manfredi.
  • E. Cesenatico
    Cesenatico is a historic Adriatic seaside town in Italy, renowned for its canal harbor designed by Leonardo da Vinci and its popular beach tourism.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbbbdf3481909abb46c71f64106a completed April 20, 2026, 10:11 a.m.
Created at: April 10, 2026, 1:29 p.m.