Triple

T794241
Position Surface form Disambiguated ID Type / Status
Subject Fiat E16981 entity
Predicate formerSubsidiary P6796 FINISHED
Object Abarth E19030 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: Abarth | Statement: [Fiat, formerSubsidiary, Abarth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abarth
Context triple: [Fiat, formerSubsidiary, Abarth]
  • A. Abarth chosen
    Abarth is an Italian performance car and racing brand known for tuning and producing sporty versions of Fiat and other compact vehicles.
  • B. Lancia
    Lancia is an Italian automobile manufacturer renowned for its historic innovations and success in motorsport, particularly rally racing.
  • C. Alfa Romeo
    Alfa Romeo is an Italian automobile manufacturer renowned for its sporty, stylish cars and long heritage in motorsport and performance engineering.
  • D. Fiat Uno
    The Fiat Uno is a compact city car produced by the Italian manufacturer Fiat, known for its practicality, fuel efficiency, and popularity in European and Latin American markets since the 1980s.
  • E. Fiat Panda
    The Fiat Panda is a popular city car produced by Italian automaker Fiat, known for its compact size, practicality, and affordability.
  • 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_69a4aa9e0f0081909d2a89387d6c08e1 completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf4f602481908f9c399063a605b9 completed March 4, 2026, 6:21 a.m.
Created at: March 1, 2026, 7:38 p.m.