Triple

T19817538
Position Surface form Disambiguated ID Type / Status
Subject Achille Paganini E476097 entity
Predicate residence P75 FINISHED
Object Genoa 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: Genoa | Statement: [Achille Paganini, residence, Genoa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Genoa
Context triple: [Achille Paganini, residence, Genoa]
  • A. Genoa chosen
    Genoa is a historic port city in northwestern Italy known for its significant maritime heritage, trade, and role as a major economic hub on the Ligurian coast.
  • B. Genoa
    Genoa is the codename for AMD’s fourth-generation EPYC server processors based on the Zen 4 architecture and the SP5 platform.
  • C. Génova
    Génova is a small municipality in Colombia’s Quindío Department, known for its coffee-growing traditions and Andean rural landscapes.
  • D. Port of Genoa
    The Port of Genoa is one of Italy’s largest and busiest seaports, serving as a major hub for commercial shipping, passenger ferries, and maritime trade in the Mediterranean.
  • E. Livorno
    Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
  • 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e654fac7b481909a19ae0d608e01d9 completed April 20, 2026, 4:31 p.m.
Created at: April 10, 2026, 1:50 p.m.