Triple

T2453963
Position Surface form Disambiguated ID Type / Status
Subject Jim Nantz E53773 entity
Predicate familyName P18 FINISHED
Object Nantz
Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
 E267734 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: Nantz | Statement: [Jim Nantz, familyName, Nantz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nantz
Context triple: [Jim Nantz, familyName, Nantz]
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • C. Choully
    Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
  • D. Bressant
    Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
  • E. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • 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: Nantz
Triple: [Jim Nantz, familyName, Nantz]
Generated description
Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nantz
Target entity description: Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • C. Choully
    Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
  • D. Bressant
    Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
  • E. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0f7f85c8190a60970b6adb7fe80 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0c7c90c8190ba5ed3cece5e049f completed March 9, 2026, 4:09 p.m.
NEDg Description generation batch_69aef5ca95dc8190b0f7f20d2128ae93 completed March 9, 2026, 4:31 p.m.
NED2 Entity disambiguation (via description) batch_69aef632e2e08190b21023cbb0f12be8 completed March 9, 2026, 4:32 p.m.
Created at: March 6, 2026, 9:44 p.m.