Triple

T5563985
Position Surface form Disambiguated ID Type / Status
Subject Tuscan dialect E145834 entity
Predicate spokenIn P2266 FINISHED
Object Livorno E67624 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: Livorno | Statement: [Tuscan dialect, spokenIn, Livorno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Livorno
Context triple: [Tuscan dialect, spokenIn, Livorno]
  • A. Livorno chosen
    Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
  • B. 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.
  • C. Savona
    Savona is a coastal city and port in the Liguria region of northwestern Italy, known historically as a strategic maritime center on the Italian Riviera.
  • D. Viareggio
    Viareggio is a coastal city in Tuscany, Italy, renowned for its seaside resorts and famous annual Carnival.
  • E. Civitavecchia
    Civitavecchia is a major Italian port city in the Lazio region that serves as the principal maritime gateway to Rome on the Tyrrhenian coast.
  • 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_69c008fdae24819081aa002ad99cd966 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02032330c819094f2bc1e8c93a5b6 completed March 22, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d0ca0088190a5d63139ba194e8e completed March 22, 2026, 8:11 p.m.
Created at: March 22, 2026, 3:36 p.m.