Triple

T19466516
Position Surface form Disambiguated ID Type / Status
Subject City of Vienne E487013 entity
Predicate twinTown P1072 FINISHED
Object Piombino 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: Piombino | Statement: [City of Vienne, twinTown, Piombino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Piombino
Context triple: [City of Vienne, twinTown, Piombino]
  • A. Piombino chosen
    Piombino is a coastal town and port in Tuscany, Italy, serving as a major mainland gateway to the island of Elba and other Tyrrhenian destinations.
  • B. Diano Marina
    Diano Marina is a coastal town and popular seaside resort on the Italian Riviera in the Liguria region of northwestern Italy.
  • C. Porto Cervo
    Porto Cervo is an exclusive luxury seaside resort and marina on Sardinia’s Costa Smeralda, renowned for its upscale tourism, yachting scene, and high-end boutiques.
  • D. Marina di Pisa
    Marina di Pisa is a coastal town in Tuscany, Italy, known as a seaside resort near Pisa on the Ligurian Sea.
  • E. Marina di Massa
    Marina di Massa is a seaside town and popular tourist resort on the Tuscan coast of northwestern Italy, known for its beaches and proximity to the Apuan Alps.
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633e1dccc819096feb1a514b9eb86 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:39 p.m.