Triple

T13528243
Position Surface form Disambiguated ID Type / Status
Subject Imari E323065 entity
Predicate hasSisterCity P919 FINISHED
Object Faenza E386577 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: Faenza | Statement: [Imari, hasSisterCity, Faenza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faenza
Context triple: [Imari, hasSisterCity, Faenza]
  • A. Faenza chosen
    Faenza is a historic city in Italy’s Emilia-Romagna region, renowned for its traditional ceramics and artistic majolica production.
  • B. Ferrara
    Ferrara is a historic city in Italy’s Emilia-Romagna region, renowned for its well-preserved Renaissance architecture and rich Jewish cultural heritage.
  • C. Ferrara
    Ferrara is an Italian surname commonly associated with people of Italian heritage, including American actor Jerry Ferrara.
  • D. Scandicci
    Scandicci is a town in central Italy located just southwest of Florence, known as a residential and industrial area within the Tuscan metropolitan region.
  • E. Modena
    Modena is a historic city in northern Italy’s Emilia-Romagna region, renowned for its balsamic vinegar, automotive heritage with Ferrari and Maserati, and its Romanesque cathedral and UNESCO-listed city center.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafb8e0cc8190b47f6aeb8ced470e completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c1ee7048190b2571364b25bd49d completed May 8, 2026, 2:36 a.m.
Created at: April 9, 2026, 9:44 p.m.