Triple

T1335113
Position Surface form Disambiguated ID Type / Status
Subject Jeep E28729 entity
Predicate hasPredecessor P97 FINISHED
Object Willys-Overland MB
The Willys-Overland MB was the iconic World War II U.S. military light utility vehicle that laid the groundwork for the modern Jeep.
 E28729 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: Willys-Overland MB | Statement: [Jeep, hasPredecessor, Willys-Overland MB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Willys-Overland MB
Context triple: [Jeep, hasPredecessor, Willys-Overland MB]
  • A. Studebaker Champion
    The Studebaker Champion was a popular mid-priced American compact car produced by Studebaker from 1939 to 1958, known for its distinctive streamlined styling and fuel efficiency.
  • B. DeSoto
    DeSoto is a suburban city in the Dallas–Fort Worth metropolitan area in North Texas.
  • C. A-Model Ford
    A-Model Ford is the common name for Ford's late-1920s Model A automobile, a popular successor to the Model T known for its improved performance and modern styling.
  • D. Jeep
    Jeep is an American automotive marque best known for its rugged sport utility vehicles and off-road capable 4x4s.
  • E. Niva
    Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
  • 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: Willys-Overland MB
Triple: [Jeep, hasPredecessor, Willys-Overland MB]
Generated description
The Willys-Overland MB was the iconic World War II U.S. military light utility vehicle that laid the groundwork for the modern Jeep.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Willys-Overland MB
Target entity description: The Willys-Overland MB was the iconic World War II U.S. military light utility vehicle that laid the groundwork for the modern Jeep.
  • A. Studebaker Champion
    The Studebaker Champion was a popular mid-priced American compact car produced by Studebaker from 1939 to 1958, known for its distinctive streamlined styling and fuel efficiency.
  • B. DeSoto
    DeSoto is a suburban city in the Dallas–Fort Worth metropolitan area in North Texas.
  • C. A-Model Ford
    A-Model Ford is the common name for Ford's late-1920s Model A automobile, a popular successor to the Model T known for its improved performance and modern styling.
  • D. Jeep chosen
    Jeep is an American automotive marque best known for its rugged sport utility vehicles and off-road capable 4x4s.
  • E. Niva
    Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
  • F. None of above.

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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1eb119881909dd5fbf728d9e8ba completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62b9bd081909dbe22cbea03f21f completed March 8, 2026, 12:43 a.m.
NEDg Description generation batch_69acc6c204a88190a3171898e6e1bb91 completed March 8, 2026, 12:45 a.m.
NED2 Entity disambiguation (via description) batch_69acc7d8df108190bf92ca5e33987d04 completed March 8, 2026, 12:50 a.m.
Created at: March 1, 2026, 7:55 p.m.