Triple

T27015746
Position Surface form Disambiguated ID Type / Status
Subject Bernd Rosemeyer E680522 entity
Predicate vehicleUsedAtDeath P59942 FINISHED
Object Auto Union streamliner
The Auto Union streamliner was an experimental, high-speed Grand Prix and land-speed record racing car of the 1930s, renowned for its advanced aerodynamics and powerful mid-mounted engine.
 E1751313 NE FINISHED

How this triple was built (3 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: Auto Union streamliner | Statement: [Bernd Rosemeyer, vehicleUsedAtDeath, Auto Union streamliner]
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: Auto Union streamliner
Triple: [Bernd Rosemeyer, vehicleUsedAtDeath, Auto Union streamliner]
Generated description
The Auto Union streamliner was an experimental, high-speed Grand Prix and land-speed record racing car of the 1930s, renowned for its advanced aerodynamics and powerful mid-mounted engine.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: vehicleUsedAtDeath
Context triple: [Bernd Rosemeyer, vehicleUsedAtDeath, Auto Union streamliner]
  • A. vehicleUsed
    Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
  • B. modeOfTransportAtDeath chosen
    Indicates the means or vehicle by which a person was traveling at the time of their death.
  • C. usedAsVehicleFor
    Indicates that one entity functions as a means of transportation or conveyance for another entity.
  • D. driverOfVictimVehicle
    Indicates that an entity is the person who was driving the vehicle occupied or owned by the victim at the time of the relevant incident.
  • E. vehicleFor
    Indicates that one entity serves as the means of transportation or conveyance for another entity.
  • F. None of above.

Provenance (6 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_69eeeb5450988190bfc9a3c012ac463a completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f625411c14819086492062e86ba8d5 completed May 2, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1229c686048190a484bbe9051fd2c2 completed May 23, 2026, 10:27 p.m.
NEDg Description generation batch_6a122ad103b08190b8eddc14442802f6 completed May 23, 2026, 10:31 p.m.
NED2 Entity disambiguation (via description) batch_6a122b4b3c488190b95edec5469dfd71 completed May 23, 2026, 10:33 p.m.
PD Predicate disambiguation batch_69f623a91b9c8190b2e2fdbc55cb89b6 completed May 2, 2026, 4:17 p.m.
Created at: April 27, 2026, 7:06 a.m.