Triple

T22531147
Position Surface form Disambiguated ID Type / Status
Subject Sète E557037 entity
Predicate twinnedWith P1072 FINISHED
Object Caltanissetta 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: Caltanissetta | Statement: [Sète, twinnedWith, Caltanissetta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caltanissetta
Context triple: [Sète, twinnedWith, Caltanissetta]
  • A. Caltanissetta chosen
    Caltanissetta is a historic inland city in central Sicily, Italy, known for its former sulfur mining industry and panoramic hilltop setting.
  • B. Cosenza
    Cosenza is a historic city in southern Italy known for its medieval old town, cultural heritage, and role as an important provincial and university center.
  • C. Gioia del Colle
    Gioia del Colle is a historic town in the Apulia region of southern Italy, known for its medieval castle, wine production, and strategic location between Bari and Taranto.
  • D. Catanzaro
    Catanzaro is a city in southern Italy known as an administrative and cultural center overlooking the Ionian Sea.
  • E. Lamezia Terme
    Lamezia Terme is a city in the Calabria region of southern Italy, known as a transportation hub and for its proximity to both the Tyrrhenian coast and the Calabrian interior.
  • 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_69e11e57483c8190b0887c4f8ff26446 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ed6734881908abbbee477dfab98 completed April 29, 2026, 1:28 a.m.
Created at: April 16, 2026, 8:51 p.m.