Triple

T4255580
Position Surface form Disambiguated ID Type / Status
Subject Sierre E95964 entity
Predicate hasTwinTown P919 FINISHED
Object Caltanissetta E87515 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: Caltanissetta | Statement: [Sierre, hasTwinTown, Caltanissetta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caltanissetta
Context triple: [Sierre, hasTwinTown, 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. Catanzaro
    Catanzaro is a city in southern Italy known as an administrative and cultural center overlooking the Ionian Sea.
  • D. Caltagirone
    Caltagirone is a historic town in Sicily renowned for its rich Baroque architecture and traditional ceramic craftsmanship.
  • E. Reggio Calabria
    Reggio Calabria is a historic coastal city in the Calabria region, known as the largest urban center at the tip of Italy’s “boot” facing Sicily across the Strait of Messina.
  • 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec1971c81908f7a72418efa8bcc completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a88a68f081909e5bae5b0414f534 completed March 14, 2026, 6:27 p.m.
Created at: March 12, 2026, 11:06 p.m.