Triple

T794214
Position Surface form Disambiguated ID Type / Status
Subject Fiat E16981 entity
Predicate notableModel P1503 FINISHED
Object Fiat 500 E16981 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: Fiat 500 | Statement: [Fiat, notableModel, Fiat 500]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fiat 500
Context triple: [Fiat, notableModel, Fiat 500]
  • A. Abarth
    Abarth is an Italian performance car and racing brand known for tuning and producing sporty versions of Fiat and other compact vehicles.
  • B. Fiat chosen
    Fiat is an Italian automobile manufacturer known for producing compact city cars and mass-market vehicles, now operating as a brand within the multinational automotive group Stellantis.
  • C. Lancia
    Lancia is an Italian automobile manufacturer renowned for its historic innovations and success in motorsport, particularly rally racing.
  • D. Volkswagen Beetle
    The Volkswagen Beetle is an iconic compact car, originally designed in the 1930s and widely recognized for its distinctive rounded shape and status as one of the best-selling cars of all time.
  • E. Fiat Ducato
    The Fiat Ducato is a popular light commercial van produced by Fiat, widely used across Europe for cargo transport, camper conversions, and other utility purposes.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a79b976c819085cd381bbd597ca5 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d7fba6c819097d8e2d962d0241f completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.