Triple

T7941072
Position Surface form Disambiguated ID Type / Status
Subject Krueger E184390 entity
Predicate hasNotableBearer P458 FINISHED
Object John Krueger
John Krueger is an American mathematician known for his work in set theory and related areas of mathematical logic.
E697228 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: John Krueger | Statement: [Krueger, hasNotableBearer, John Krueger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Krueger
Context triple: [Krueger, hasNotableBearer, John Krueger]
  • A. Michael O’Keefe
    Michael O’Keefe is an American actor best known for his role as young caddie Danny Noonan in the classic comedy film "Caddyshack."
  • B. Chris DeWolfe
    Chris DeWolfe is an American entrepreneur best known as the co-creator and former CEO of the pioneering social networking site MySpace.
  • C. Turk Malloy
    Turk Malloy is a skilled driver and member of Danny Ocean’s crew in the "Ocean's" heist film series.
  • D. Tom Ryan
    Tom Ryan is the central protagonist of the television series "The Unit," depicted as a highly skilled and seasoned leader of an elite U.S. Army special operations team.
  • E. John Poindexter
    John Poindexter is a retired U.S. Navy admiral and government official best known for serving as National Security Advisor under President Ronald Reagan and for his central role in the Iran-Contra affair.
  • 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: John Krueger
Triple: [Krueger, hasNotableBearer, John Krueger]
Generated description
John Krueger is an American mathematician known for his work in set theory and related areas of mathematical logic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John Krueger
Target entity description: John Krueger is an American mathematician known for his work in set theory and related areas of mathematical logic.
  • A. Michael O’Keefe
    Michael O’Keefe is an American actor best known for his role as young caddie Danny Noonan in the classic comedy film "Caddyshack."
  • B. Chris DeWolfe
    Chris DeWolfe is an American entrepreneur best known as the co-creator and former CEO of the pioneering social networking site MySpace.
  • C. Turk Malloy
    Turk Malloy is a skilled driver and member of Danny Ocean’s crew in the "Ocean's" heist film series.
  • D. Tom Ryan
    Tom Ryan is the central protagonist of the television series "The Unit," depicted as a highly skilled and seasoned leader of an elite U.S. Army special operations team.
  • E. John Poindexter
    John Poindexter is a retired U.S. Navy admiral and government official best known for serving as National Security Advisor under President Ronald Reagan and for his central role in the Iran-Contra affair.
  • 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_69ca8291c2008190b1b8832c87814bcf completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b0ac8bc8190b4e4f79b15c316b3 completed March 31, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c1265008190a97ccedf92f9234e completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb5f22f89c8190a98208bf096a2427 completed March 31, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69cb76d2dff8819085ad9e10baad1537 completed March 31, 2026, 7:25 a.m.
Created at: March 30, 2026, 5:08 p.m.