Triple

T2578153
Position Surface form Disambiguated ID Type / Status
Subject Biennio Rosso E57024 entity
Predicate location P40 FINISHED
Object Genoa E19522 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: Genoa | Statement: [Biennio Rosso, location, Genoa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Genoa
Context triple: [Biennio Rosso, location, 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. Livorno
    Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
  • C. Port of La Spezia
    The Port of La Spezia is a major commercial and container seaport in northwestern Italy, serving as an important maritime gateway for trade in the Mediterranean region.
  • D. La Spezia
    La Spezia is a port city in northwestern Italy known as a major naval base and gateway to the Cinque Terre on the Ligurian coast.
  • E. San Remigio
    San Remigio is a coastal municipality in the province of Cebu in the Philippines, known for its long stretch of white-sand beaches and dive spots.
  • 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_69ab4a4dca6481908c301f8e317396e7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3a86f9881908df29a7caaf9a7df completed March 7, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce7c4910819095b81e419de10566 completed March 10, 2026, 7:55 a.m.
Created at: March 6, 2026, 9:49 p.m.