Triple

T2628117
Position Surface form Disambiguated ID Type / Status
Subject Roberto Farinacci E59167 entity
Predicate residence P75 FINISHED
Object Cremona E126825 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: Cremona | Statement: [Roberto Farinacci, residence, Cremona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cremona
Context triple: [Roberto Farinacci, residence, 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. Bergamo
    Bergamo is a historic city in northern Italy known for its medieval walled upper town, rich artistic heritage, and strategic location at the foothills of the Alps.
  • C. Brescia
    Brescia is a historic industrial and cultural city in northern Italy, known for its Roman and medieval architecture and its role as an economic hub.
  • D. 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.
  • E. Mantua
    Mantua is a small Cuban town and municipality located in the western part of Pinar del Río Province.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c2e3d88190a972f58356f282cc completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0862d08e48190a40af283184991ee completed March 10, 2026, 8:59 p.m.
Created at: March 6, 2026, 9:50 p.m.