Triple

T16260861
Position Surface form Disambiguated ID Type / Status
Subject Wolf Racing E394749 entity
Predicate carModel P32674 FINISHED
Object Wolf WR7
Wolf WR7 is a late-1970s Formula One racing car built by the Walter Wolf Racing team to compete in the FIA World Championship.
E1211122 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: Wolf WR7 | Statement: [Wolf Racing, carModel, Wolf WR7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolf WR7
Context triple: [Wolf Racing, carModel, Wolf WR7]
  • A. Wolf WR2
    Wolf WR2 is a historic prototype racing car developed by Wolf Racing for sports car competition.
  • B. Wolf WR5
    Wolf WR5 is a historic Formula One racing car built by Walter Wolf Racing that competed in the late 1970s.
  • C. Wolf WR3
    Wolf WR3 is a historic Formula One racing car from the late 1970s, campaigned by the Walter Wolf Racing team in Grand Prix competition.
  • D. Wolf WR1
    Wolf WR1 is a late-1970s Formula One racing car that competed under the Walter Wolf Racing team, notably achieving multiple Grand Prix victories.
  • E. Trailhawk
    Trailhawk is an off-road-focused trim level in Jeep’s lineup, featuring enhanced four-wheel-drive capability and rugged styling elements.
  • 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: Wolf WR7
Triple: [Wolf Racing, carModel, Wolf WR7]
Generated description
Wolf WR7 is a late-1970s Formula One racing car built by the Walter Wolf Racing team to compete in the FIA World Championship.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wolf WR7
Target entity description: Wolf WR7 is a late-1970s Formula One racing car built by the Walter Wolf Racing team to compete in the FIA World Championship.
  • A. Wolf WR2
    Wolf WR2 is a historic prototype racing car developed by Wolf Racing for sports car competition.
  • B. Wolf WR5
    Wolf WR5 is a historic Formula One racing car built by Walter Wolf Racing that competed in the late 1970s.
  • C. Wolf WR3
    Wolf WR3 is a historic Formula One racing car from the late 1970s, campaigned by the Walter Wolf Racing team in Grand Prix competition.
  • D. Wolf WR1
    Wolf WR1 is a late-1970s Formula One racing car that competed under the Walter Wolf Racing team, notably achieving multiple Grand Prix victories.
  • E. Trailhawk
    Trailhawk is an off-road-focused trim level in Jeep’s lineup, featuring enhanced four-wheel-drive capability and rugged styling elements.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245c3e5388190942b0237ab5d1f0f completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a003c48c5cc8190ba99154e99942316 completed May 10, 2026, 8:05 a.m.
NEDg Description generation batch_6a003d449da881908eb66b2e9c20729e completed May 10, 2026, 8:09 a.m.
NED2 Entity disambiguation (via description) batch_6a003d9c6f1881909c0155c0fd3f9872 completed May 10, 2026, 8:11 a.m.
Created at: April 10, 2026, 5:04 a.m.