Triple

T20084937
Position Surface form Disambiguated ID Type / Status
Subject Galeazzo Alessi E500100 entity
Predicate workLocation P7 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: [Galeazzo Alessi, workLocation, Genoa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Genoa
Context triple: [Galeazzo Alessi, workLocation, 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655a2d2c81908a6b8fd2f209a825 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.