Triple

T18927311
Position Surface form Disambiguated ID Type / Status
Subject Klausen E463007 entity
Predicate officialName P66 FINISHED
Object Chiusa 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: Chiusa | Statement: [Klausen, officialName, Chiusa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chiusa
Context triple: [Klausen, officialName, Chiusa]
  • A. Chiusa chosen
    Chiusa is a small historic town in South Tyrol, northern Italy, known for its picturesque medieval center and Alpine surroundings.
  • B. Chiusi
    Chiusi is an ancient town in central Italy renowned as one of the principal cities of the Etruscan civilization and noted for its rich archaeological heritage.
  • C. Clausura
    Clausura is the closing half of a split football season format commonly used in Latin American leagues, following the Apertura tournament.
  • D. Chiusi Scalo
    Chiusi Scalo is a small Italian town in Tuscany that serves as the modern railway and commercial district for the historic hilltop city of Chiusi.
  • E. Chiusaforte
    Chiusaforte is a small mountain town in northeastern Italy’s Friuli-Venezia Giulia region, known as a gateway to the surrounding Alpine landscapes and ski areas.
  • 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c9bc36588190ae9cc3b8abf8afd4 completed April 20, 2026, 6:37 a.m.
Created at: April 10, 2026, 11:59 a.m.