Triple

T17160535
Position Surface form Disambiguated ID Type / Status
Subject ZF Friedrichshafen E416463 entity
Predicate hasSubsidiary P254 FINISHED
Object WABCO
WABCO is a global supplier of braking, stability, suspension, and transmission automation systems for commercial vehicles and trailers.
 E1254824 NE FINISHED

How this triple was built (4 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: WABCO | Statement: [ZF Friedrichshafen, hasSubsidiary, WABCO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WABCO
Context triple: [ZF Friedrichshafen, hasSubsidiary, WABCO]
  • A. Meritor
    Meritor is the abbreviated name of Meritor Savings Bank, FSB, a former U.S. financial institution that provided consumer and commercial banking services.
  • B. PACCAR
    PACCAR is a major American manufacturer of commercial trucks and related heavy-duty vehicles headquartered in Bellevue, Washington.
  • C. Eaton
    Eaton is a small town located within Madison County in the state of New York, United States.
  • D. Eaton
    Eaton is a surname most notably associated with American decathlete and Olympic gold medalist Ashton Eaton.
  • E. Eaton
    Eaton is the namesake of the Eaton Professor of the Science of Government at Harvard University, an endowed academic chair in political science and government studies.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: WABCO
Triple: [ZF Friedrichshafen, hasSubsidiary, WABCO]
Generated description
WABCO is a global supplier of braking, stability, suspension, and transmission automation systems for commercial vehicles and trailers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WABCO
Target entity description: WABCO is a global supplier of braking, stability, suspension, and transmission automation systems for commercial vehicles and trailers.
  • A. Meritor
    Meritor is the abbreviated name of Meritor Savings Bank, FSB, a former U.S. financial institution that provided consumer and commercial banking services.
  • B. PACCAR
    PACCAR is a major American manufacturer of commercial trucks and related heavy-duty vehicles headquartered in Bellevue, Washington.
  • C. Eaton
    Eaton is a small town located within Madison County in the state of New York, United States.
  • D. Eaton
    Eaton is a surname most notably associated with American decathlete and Olympic gold medalist Ashton Eaton.
  • E. Eaton
    Eaton is the namesake of the Eaton Professor of the Science of Government at Harvard University, an endowed academic chair in political science and government studies.
  • F. None of above. chosen

Provenance (5 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f911114481909c865b2e2d3b3a2b completed April 18, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0148376bc081908372366203a27fa8 completed May 11, 2026, 3:08 a.m.
NEDg Description generation batch_6a014b5691a881908fdad49f7dadc76c completed May 11, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_6a014bbc921081909c39cd6d11400b56 completed May 11, 2026, 3:23 a.m.
Created at: April 10, 2026, 5:37 a.m.