Triple

T32732305
Position Surface form Disambiguated ID Type / Status
Subject Little Bastard E836985 entity
Predicate hasCollisionDriverOfOtherCar P184088 FINISHED
Object Donald Turnupseed
Donald Turnupseed was the young American driver whose car collided with James Dean’s Porsche in the 1955 crash that killed the actor.
 E2018010 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: Donald Turnupseed | Statement: [Little Bastard, hasCollisionDriverOfOtherCar, Donald Turnupseed]
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: Donald Turnupseed
Triple: [Little Bastard, hasCollisionDriverOfOtherCar, Donald Turnupseed]
Generated description
Donald Turnupseed was the young American driver whose car collided with James Dean’s Porsche in the 1955 crash that killed the actor.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasCollisionDriverOfOtherCar
Context triple: [Little Bastard, hasCollisionDriverOfOtherCar, Donald Turnupseed]
  • A. driversInCollision chosen
    Indicates that the related entities are drivers who were involved in the same vehicle collision or traffic accident.
  • B. catcherInCollision
    Indicates that an entity serves as the catcher involved in a collision event with another entity.
  • C. alsoAssociatedWithDriver
    Indicates that an entity has an additional or secondary association with a specified driver, beyond any primary or previously stated driver relationship.
  • D. hasVehicleCrossing
    Indicates that a location or route includes a designated crossing point specifically intended for vehicles to pass through.
  • E. 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.
  • 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_69f34935fb048190ad4967420581f835 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_6a037cad051c8190b28b354b89208574 completed May 12, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a349edcb3708190a668ce20a12a5a6f completed June 19, 2026, 1:43 a.m.
NEDg Description generation batch_6a349f8044248190bb242457861c365e completed June 19, 2026, 1:46 a.m.
NED2 Entity disambiguation (via description) batch_6a349fcf783881909cb072d0bbdbfce9 completed June 19, 2026, 1:47 a.m.
PD Predicate disambiguation batch_6a0379f0cbe481909b4b8fc6cbe297f0 completed May 12, 2026, 7:05 p.m.
Created at: May 1, 2026, 1:11 a.m.