Triple

T15550567
Position Surface form Disambiguated ID Type / Status
Subject Poggio Nativo E370731 entity
Predicate sharesBorderWith P224 FINISHED
Object Frasso Sabino E344584 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: Frasso Sabino | Statement: [Poggio Nativo, sharesBorderWith, Frasso Sabino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frasso Sabino
Context triple: [Poggio Nativo, sharesBorderWith, Frasso Sabino]
  • A. Frasso Sabino chosen
    Frasso Sabino is a small Italian municipality in the Lazio region, known for its medieval hilltop setting and historic architecture within the Province of Rieti.
  • B. Pino
    Pino is an Italian diminutive form of the given name Giuseppe, commonly used as a familiar or affectionate nickname.
  • C. Pino
    Pino is the former historic name of the present-day Town of Loomis in Placer County, California.
  • D. Frasso Telesino
    Frasso Telesino is a small Italian town in the Campania region known for its historic hilltop setting and surrounding rural landscapes.
  • E. Treiso
    Treiso is a small village in Italy’s Piedmont region renowned for its production of high-quality Barbaresco wines from Nebbiolo grapes.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a9551288190a583e8291c35f521 completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455dfbcc8190a93e90c59b2d3045 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:08 a.m.