Triple

T17894982
Position Surface form Disambiguated ID Type / Status
Subject Fiat Ferroviaria E447408 entity
Predicate notableProduct P1448 FINISHED
Object ETR 460 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: ETR 460 | Statement: [Fiat Ferroviaria, notableProduct, ETR 460]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ETR 460
Context triple: [Fiat Ferroviaria, notableProduct, ETR 460]
  • A. ETR 460 chosen
    ETR 460 is an Italian high-speed tilting trainset used primarily for fast intercity passenger services.
  • B. ETR 450
    The ETR 450 is an Italian high-speed tilting trainset introduced in the late 1980s for Trenitalia’s Eurostar services, notable as one of the first production Pendolino trains.
  • C. ETR 470
    ETR 470 is an Italian-designed high-speed tilting electric multiple unit train used primarily for international EuroCity services in Europe.
  • D. ETR 600
    The ETR 600 is a class of Italian high-speed tilting electric multiple unit trains used for fast intercity and international services.
  • E. ETR 480
    ETR 480 is an Italian high-speed tilting electric multiple unit train used primarily for long-distance passenger services in Europe.
  • 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_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d7eb4f48190951e26975b57873b completed April 19, 2026, 9:16 a.m.
Created at: April 10, 2026, 10:19 a.m.