Triple

T18456686
Position Surface form Disambiguated ID Type / Status
Subject SS26 E450918 entity
Predicate connectsCity P4245 FINISHED
Object Chivasso 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: Chivasso | Statement: [SS26, connectsCity, Chivasso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chivasso
Context triple: [SS26, connectsCity, Chivasso]
  • A. Chivasso chosen
    Chivasso is a town and comune in the Piedmont region of northwestern Italy, situated near Turin along the Po River.
  • B. Collecchio
    Collecchio is a municipality in the Emilia-Romagna region of northern Italy, known for its agricultural production and food industry, particularly in relation to Parma’s renowned culinary traditions.
  • C. Pioltello
    Pioltello is a municipality in the Metropolitan City of Milan in Lombardy, northern Italy, known as a residential and industrial suburb of Milan.
  • D. Cotignola
    Cotignola is a small Italian town in the Emilia-Romagna region, known for its historic center and agricultural surroundings.
  • E. Schio
    Schio is an industrial town in northeastern Italy known historically for its textile production and location in the Veneto region.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5264ce5948190b57baa2ea71297a9 completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:31 a.m.