Triple

T9273697
Position Surface form Disambiguated ID Type / Status
Subject Teano E222891 entity
Predicate province P604 FINISHED
Object Caserta E126810 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: Caserta | Statement: [Teano, province, Caserta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caserta
Context triple: [Teano, province, Caserta]
  • A. Caserta chosen
    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.
  • B. Gaeta
    Gaeta is a historic coastal town in central Italy known for its scenic Gulf of Gaeta, medieval fortifications, and strategic military and maritime significance.
  • C. Potenza
    Potenza is a historic city in southern Italy that serves as the administrative and cultural center of the Basilicata region.
  • D. Salerno
    Salerno is a historic port city in southern Italy, known for its strategic role in World War II Allied landings and its position on the Tyrrhenian Sea near the Amalfi Coast.
  • E. Campobasso
    Campobasso is a historic city in southern-central Italy that serves as the capital of the Molise region, known for its medieval castle and traditional craftsmanship.
  • 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_69ca841ffe208190aa7bcffbef2f8379 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0788e87c81909ccda40d94cc6705 completed April 1, 2026, 11:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0b1f57db881908a42ad5b042d0872 completed April 4, 2026, 6:38 a.m.
Created at: March 30, 2026, 7:33 p.m.