Triple

T6253620
Position Surface form Disambiguated ID Type / Status
Subject Province of Ravenna E140106 entity
Predicate contains P35 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: [Province of Ravenna, contains, Faenza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faenza
Context triple: [Province of Ravenna, contains, 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. 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.
  • D. Pesaro
    Pesaro is a coastal city on Italy’s Adriatic Sea, known for its Renaissance architecture, seaside resorts, and as the birthplace of composer Gioachino Rossini.
  • E. Prato
    Prato is a historic Tuscan city in central Italy known for its textile industry, medieval architecture, and cultural heritage.
  • 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_69c008b4858c819095b0199114a9a87b completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063625608819081f5422112c80ce5 completed March 22, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f6514948190a5562201e7b36e27 completed March 28, 2026, 1:31 a.m.
Created at: March 22, 2026, 4:24 p.m.