Triple

T14739084
Position Surface form Disambiguated ID Type / Status
Subject Fiuggi E346294 entity
Predicate nearbyCity P350 FINISHED
Object Frosinone E101395 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: Frosinone | Statement: [Fiuggi, nearbyCity, Frosinone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frosinone
Context triple: [Fiuggi, nearbyCity, Frosinone]
  • A. Frosinone chosen
    Frosinone is a city in central Italy that serves as the capital of the province of the same name within the Lazio region.
  • B. Isernia
    Isernia is a historic town and provincial capital in the Molise region of southern-central Italy, known for its ancient Samnite and Roman roots.
  • C. Rieti
    Rieti is a historic town in central Italy often considered the geographical center of the country and known for its medieval architecture and proximity to the Apennine Mountains.
  • D. Lazio
    Lazio is a major professional football club based in Rome, Italy, known for competing in Serie A and for its passionate fan base and historic rivalry with AS Roma.
  • E. Lazio
    Lazio is a central Italian region best known for encompassing the nation’s capital, Rome, and its rich historical and cultural heritage.
  • 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_69fe64ee4284819093db172023e9fe87 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:29 a.m.