Triple

T20022019
Position Surface form Disambiguated ID Type / Status
Subject Autostrada A1 E494884 entity
Predicate passesNearCity P3945 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: [Autostrada A1, passesNearCity, Caserta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caserta
Context triple: [Autostrada A1, passesNearCity, 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66288fc18819083833b55c5e069a6 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:35 p.m.