Triple

T22009975
Position Surface form Disambiguated ID Type / Status
Subject Caserta railway station E543549 entity
Predicate locatedIn P40 FINISHED
Object Caserta 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: Caserta | Statement: [Caserta railway station, locatedIn, Caserta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caserta
Context triple: [Caserta railway station, locatedIn, 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. Aversa
    Aversa is a historic city in southern Italy’s Campania region, known for its medieval origins and proximity to Naples.
  • C. 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.
  • D. Potenza
    Potenza is a historic city in southern Italy that serves as the administrative and cultural center of the Basilicata region.
  • E. Potenza
    Potenza is a river in the Marche region of central Italy that flows through the Province of Macerata before reaching the Adriatic Sea.
  • 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_69e11e2db934819095556760c7d85e4d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127a376048190a78ba7efd303b58a completed April 28, 2026, 9:33 p.m.
Created at: April 16, 2026, 8:22 p.m.