Triple

T12270843
Position Surface form Disambiguated ID Type / Status
Subject Kenneth Prewitt E292465 entity
Predicate familyName P18 FINISHED
Object Prewitt
Prewitt is a surname of English origin borne by various notable individuals across fields such as academia, politics, and the arts.
 E975786 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: Prewitt | Statement: [Kenneth Prewitt, familyName, Prewitt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Prewitt
Context triple: [Kenneth Prewitt, familyName, Prewitt]
  • A. Sobel
    Sobel is a surname most notably associated with American science writer Dava Sobel, known for her popular books on the history of science and astronomy.
  • B. Grünwald–Letnikov derivative
    The Grünwald–Letnikov derivative is a fundamental definition of fractional differentiation based on limit processes and finite differences, widely used as a foundation for fractional calculus.
  • C. Fagerstrand
    Fagerstrand is a village in Nesodden municipality in Viken county, Norway, located along the Oslofjord.
  • D. Pami
    Pami was a pharaoh of Egypt’s Twenty-second Dynasty, a Libyan-origin ruler known from the Third Intermediate Period.
  • E. Moravec
    Moravec is a Czech surname most notably associated with figures such as mountaineer Fritz Moravec and roboticist Hans Moravec.
  • 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: Prewitt
Triple: [Kenneth Prewitt, familyName, Prewitt]
Generated description
Prewitt is a surname of English origin borne by various notable individuals across fields such as academia, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Prewitt
Target entity description: Prewitt is a surname of English origin borne by various notable individuals across fields such as academia, politics, and the arts.
  • A. Sobel
    Sobel is a surname most notably associated with American science writer Dava Sobel, known for her popular books on the history of science and astronomy.
  • B. Grünwald–Letnikov derivative
    The Grünwald–Letnikov derivative is a fundamental definition of fractional differentiation based on limit processes and finite differences, widely used as a foundation for fractional calculus.
  • C. Fagerstrand
    Fagerstrand is a village in Nesodden municipality in Viken county, Norway, located along the Oslofjord.
  • D. Pami
    Pami was a pharaoh of Egypt’s Twenty-second Dynasty, a Libyan-origin ruler known from the Third Intermediate Period.
  • E. Moravec
    Moravec is a Czech surname most notably associated with figures such as mountaineer Fritz Moravec and roboticist Hans Moravec.
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cdea6e881908e13f8259bad6ddc completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e6981b48190a0fc5a571c425be1 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f622de74f0819096c5f5bf6f938fe7 completed May 2, 2026, 4:14 p.m.
NED2 Entity disambiguation (via description) batch_69f62379746c8190bc9da48775b86dfa completed May 2, 2026, 4:16 p.m.
Created at: April 8, 2026, 9:52 p.m.