Triple

T5895996
Position Surface form Disambiguated ID Type / Status
Subject courts of appeal of Italy E131101 entity
Predicate hasSeatIn P3522 FINISHED
Object Potenza E350143 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: Potenza | Statement: [courts of appeal of Italy, hasSeatIn, Potenza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Potenza
Context triple: [courts of appeal of Italy, hasSeatIn, Potenza]
  • A. Potenza chosen
    Potenza is a historic city in southern Italy that serves as the administrative and cultural center of the Basilicata region.
  • 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. Caserta
    Caserta is a city in southern Italy’s Campania region, best known for its grand 18th-century Royal Palace (Reggia di Caserta), a UNESCO World Heritage Site.
  • D. Barletta
    Barletta is a historic coastal city in the Apulia region of southern Italy, known for its medieval architecture and role as a provincial capital.
  • E. Catanzaro
    Catanzaro is a city in southern Italy known as an administrative and cultural center overlooking the Ionian Sea.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036f4b56c8190aa52c9460eae8fbe completed March 22, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e399f2ec81908e2e38b9fbf8b56a completed March 27, 2026, 1:55 a.m.
Created at: March 22, 2026, 3:58 p.m.