Triple

T6747510
Position Surface form Disambiguated ID Type / Status
Subject 1930 FIFA World Cup E154254 entity
Predicate ballUsed P3186 FINISHED
Object T-Model
The T-Model was an early leather football design used in top-level international competitions, including the inaugural FIFA World Cup.
 E615768 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: T-Model | Statement: [1930 FIFA World Cup, ballUsed, T-Model]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: T-Model
Context triple: [1930 FIFA World Cup, ballUsed, T-Model]
  • A. Modell
    Modell is the surname of Art Modell, the influential former owner of the NFL’s Cleveland Browns and Baltimore Ravens.
  • B. 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.
  • C. T-29
    T-29 is a U.S. Air Force military trainer aircraft variant of the Convair 240 series used primarily for navigation and radar training.
  • D. M-Line Trolley
    M-Line Trolley is a heritage streetcar system operating in Dallas, Texas, providing free public transportation along the McKinney Avenue and Uptown areas.
  • E. Mack
    Mack is a given name commonly used as a masculine first name or nickname in English-speaking countries.
  • 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: T-Model
Triple: [1930 FIFA World Cup, ballUsed, T-Model]
Generated description
The T-Model was an early leather football design used in top-level international competitions, including the inaugural FIFA World Cup.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: T-Model
Target entity description: The T-Model was an early leather football design used in top-level international competitions, including the inaugural FIFA World Cup.
  • A. Modell
    Modell is the surname of Art Modell, the influential former owner of the NFL’s Cleveland Browns and Baltimore Ravens.
  • B. 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.
  • C. T-29
    T-29 is a U.S. Air Force military trainer aircraft variant of the Convair 240 series used primarily for navigation and radar training.
  • D. M-Line Trolley
    M-Line Trolley is a heritage streetcar system operating in Dallas, Texas, providing free public transportation along the McKinney Avenue and Uptown areas.
  • E. Mack
    Mack is a given name commonly used as a masculine first name or nickname in English-speaking countries.
  • 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_69c6880ef37881909268a5a7299b9293 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1d785dc81909c033084d2068568 completed March 27, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70b15ded88190a36fb86093ba5a3c completed March 27, 2026, 10:56 p.m.
NEDg Description generation batch_69c70c334a90819084bb0b25bbc112cc completed March 27, 2026, 11:01 p.m.
NED2 Entity disambiguation (via description) batch_69c70d0fcbc08190b3a7d0de3c634a5f completed March 27, 2026, 11:04 p.m.
Created at: March 27, 2026, 2:11 p.m.