Triple

T9845243
Position Surface form Disambiguated ID Type / Status
Subject Champ Clark E239324 entity
Predicate nickname P55 FINISHED
Object Champ
Champ is the nickname of Champ Clark, an influential early 20th-century American Democratic politician who served as Speaker of the U.S. House of Representatives.
 E824773 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: Champ | Statement: [Champ Clark, nickname, Champ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Champ
Context triple: [Champ Clark, nickname, Champ]
  • A. Champ
    Champ is a supporting character in the action-spy film "Kingsman: The Golden Circle," serving as a high-ranking member of the American Statesman organization.
  • B. Champ
    Champ is the costumed bulldog mascot representing Louisiana Tech University's athletic teams and school spirit.
  • C. Champ
    Champ is the Dallas Mavericks’ horse-themed team mascot known for energizing crowds at their NBA games.
  • D. Champ Kind
    Champ Kind is a loud, boisterous sportscaster and member of the Channel 4 news team in the comedy film "Anchorman: The Legend of Ron Burgundy," known for his over-the-top enthusiasm and catchphrases.
  • E. The Champ
    The Champ is a 1931 American drama film directed by King Vidor, renowned for its poignant story of a washed-up boxer and his devoted young son.
  • 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: Champ
Triple: [Champ Clark, nickname, Champ]
Generated description
Champ is the nickname of Champ Clark, an influential early 20th-century American Democratic politician who served as Speaker of the U.S. House of Representatives.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Champ
Target entity description: Champ is the nickname of Champ Clark, an influential early 20th-century American Democratic politician who served as Speaker of the U.S. House of Representatives.
  • A. Champ
    Champ is the Dallas Mavericks’ horse-themed team mascot known for energizing crowds at their NBA games.
  • B. Champ
    Champ is a supporting character in the action-spy film "Kingsman: The Golden Circle," serving as a high-ranking member of the American Statesman organization.
  • C. Champ
    Champ is the costumed bulldog mascot representing Louisiana Tech University's athletic teams and school spirit.
  • D. Champ Kind
    Champ Kind is a loud, boisterous sportscaster and member of the Channel 4 news team in the comedy film "Anchorman: The Legend of Ron Burgundy," known for his over-the-top enthusiasm and catchphrases.
  • E. The Champ
    The Champ is a 1931 American drama film directed by King Vidor, renowned for its poignant story of a washed-up boxer and his devoted young son.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb35ff7848190a8a717773d8654b9 completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5e1b67c8190ad7b57ea423511d8 completed April 5, 2026, 3:24 a.m.
NEDg Description generation batch_69d1d6a385ac8190b5dd11adfbb7578d completed April 5, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69d1d75210f4819096ee05a8b870581e completed April 5, 2026, 3:30 a.m.
Created at: March 30, 2026, 8:33 p.m.