Triple

T15427035
Position Surface form Disambiguated ID Type / Status
Subject Turin–Cuneo railway E369537 entity
Predicate endPoint P390 FINISHED
Object Cuneo E235587 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: Cuneo | Statement: [Turin–Cuneo railway, endPoint, Cuneo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuneo
Context triple: [Turin–Cuneo railway, endPoint, Cuneo]
  • A. Cuneo chosen
    Cuneo is a city in the Piedmont region of northwestern Italy, known for its Alpine setting, agricultural traditions, and use of the Piedmontese language.
  • B. Biella
    Biella is a city in the Piedmont region of northern Italy, known for its textile industry and Alpine foothill setting.
  • C. Alessandria
    Alessandria is a city in the Piedmont region of northwestern Italy, known as an important industrial and transportation hub.
  • D. Villafranca Piemonte
    Villafranca Piemonte is a municipality in the Piedmont region of northwestern Italy, historically associated with the House of Savoy.
  • E. Ivrea
    Ivrea is a historic town in Italy’s Piedmont region, known for its medieval architecture, industrial heritage, and the famous Battle of the Oranges carnival.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ec1fb288190a3625b8e4f487dd1 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d40d3388190b1bd724238f928b1 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 3:20 a.m.