Triple

T8929972
Position Surface form Disambiguated ID Type / Status
Subject MAN Truck & Bus E212627 entity
Predicate parentOrganization P254 FINISHED
Object TRATON SE E38078 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: TRATON SE | Statement: [MAN Truck & Bus, parentOrganization, TRATON SE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TRATON SE
Context triple: [MAN Truck & Bus, parentOrganization, TRATON SE]
  • A. Traton chosen
    Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
  • B. Casa Transports SA
    Casa Transports SA is the public company responsible for managing and developing urban transport infrastructure and services in Casablanca, Morocco, including the city’s tramway network.
  • C. Systra
    Systra is a global engineering and consulting firm specializing in mass transit and rail infrastructure projects.
  • D. Suter
    Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
  • E. Total S.A.
    Total S.A. was the former name of TotalEnergies, a major French multinational energy company involved in oil, gas, and increasingly renewable energy.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6676d5d881908ce78cbb5561a68b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba63544081909394500f28b34ccb completed April 3, 2026, 1:02 p.m.
Created at: March 30, 2026, 6:57 p.m.