Triple

T22298973
Position Surface form Disambiguated ID Type / Status
Subject CR E551201 entity
Predicate jurisdiction P82 FINISHED
Object City of Cremona 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: City of Cremona | Statement: [CR, jurisdiction, City of Cremona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Cremona
Context triple: [CR, jurisdiction, City of Cremona]
  • A. Cremona chosen
    Cremona is a historic city in northern Italy renowned for its tradition of violin making and its well-preserved medieval architecture.
  • B. Pavia
    Pavia is a municipality in the Philippine province of Iloilo known for its suburban character and proximity to Iloilo City.
  • C. Pavia
    Pavia is a historic city in northern Italy, known for its ancient university, medieval architecture, and significant role in Lombardy’s cultural and academic life.
  • D. Monzino
    Monzino is an Italian surname most notably associated with entrepreneur and mountaineer Guido Monzino, known for his explorations and cultural patronage.
  • E. Bobbio
    Bobbio is an Italian surname most notably borne by the influential 20th-century legal philosopher and political theorist Norberto Bobbio.
  • 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_69e11e45fb848190a1b2ae21296e3a5f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15722c3348190b63eb49764ef132d completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:41 p.m.