Triple

T21784916
Position Surface form Disambiguated ID Type / Status
Subject Leopoldsburg E537809 entity
Predicate hasTwinTown P919 FINISHED
Object Collegno 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: Collegno | Statement: [Leopoldsburg, hasTwinTown, Collegno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Collegno
Context triple: [Leopoldsburg, hasTwinTown, Collegno]
  • A. Collegno chosen
    Collegno is a municipality in the Metropolitan City of Turin in northern Italy, known as a residential and industrial suburb of Turin.
  • B. Rosciano
    Rosciano is a small Italian municipality in the Abruzzo region, known for its rural landscape and traditional local agriculture.
  • C. 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.
  • D. Buccinasco
    Buccinasco is a suburban municipality in northern Italy located just southwest of Milan, known for its residential character and proximity to the Lombard capital.
  • E. Cuneo
    Cuneo is a city in the Piedmont region of northwestern Italy, known for its Alpine setting, agricultural traditions, and use of the Piedmontese language.
  • 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_69e0c47198f881908cb0d237266c10e9 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f04630f4f08190910b9e499a4249ca completed April 28, 2026, 5:31 a.m.
Created at: April 16, 2026, 6:52 p.m.