Triple

T15443115
Position Surface form Disambiguated ID Type / Status
Subject Sergio Marchionne E369956 entity
Predicate parentOrganizationLed P30657 FINISHED
Object CNH Industrial E609723 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: CNH Industrial | Statement: [Sergio Marchionne, parentOrganizationLed, CNH Industrial]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CNH Industrial
Context triple: [Sergio Marchionne, parentOrganizationLed, CNH Industrial]
  • A. CNH Industrial chosen
    CNH Industrial is a global capital goods company known for manufacturing agricultural and construction equipment, commercial vehicles, and powertrain solutions.
  • B. CNH
    CNH is the offshore-traded version of China’s currency, the yuan, used primarily in international markets outside mainland China.
  • C. MAN Nutzfahrzeuge AG
    MAN Nutzfahrzeuge AG was the former name of the German commercial vehicle manufacturer now known as MAN Truck & Bus, a major producer of trucks and buses in Europe.
  • D. Daimler Truck AG
    Daimler Truck AG is a leading global commercial vehicle manufacturer specializing in trucks and buses, formed as an independent company after its separation from the former Daimler AG.
  • E. Deutz AG
    Deutz AG is a German manufacturer best known for producing internal combustion engines, particularly for industrial and agricultural applications.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef55f5c8190a32b1b6ad1daf454 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cf7ce7c8190810ef35b6e37254d completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:21 a.m.