Triple

T14739110
Position Surface form Disambiguated ID Type / Status
Subject Ciociaria E346295 entity
Predicate hasMajorTown P316 FINISHED
Object Arpino E734716 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: Arpino | Statement: [Ciociaria, hasMajorTown, Arpino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arpino
Context triple: [Ciociaria, hasMajorTown, Arpino]
  • A. Arpino chosen
    Arpino is a historic town in central Italy, traditionally known as the birthplace of the Roman statesman Cicero.
  • B. Minturno
    Minturno is a historic town in the Lazio region of central Italy, known for its ancient Roman ruins and scenic position near the Tyrrhenian coast.
  • C. Magliano de' Marsi
    Magliano de' Marsi is a small town in the Abruzzo region of central Italy, known for its historic architecture and scenic setting within the Apennine mountain landscape.
  • D. Paliano
    Paliano is a historic town in the Lazio region of central Italy, traditionally linked to the noble Colonna family.
  • E. Ceccano
    Ceccano is a historic town and comune in the Lazio region of central Italy, situated in the Province of Frosinone along the Sacco River.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec73264848190be23c5f0260cbe13 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ebbc67c8190bd930a2773edb5b2 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 1:29 a.m.