Triple

T9429343
Position Surface form Disambiguated ID Type / Status
Subject Michels E227331 entity
Predicate hasNotableBearer P458 FINISHED
Object Paul Michels
Paul Michels is a notable individual recognized for achievements significant enough to be recorded under the surname Michels.
 E828866 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: Paul Michels | Statement: [Michels, hasNotableBearer, Paul Michels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paul Michels
Context triple: [Michels, hasNotableBearer, Paul Michels]
  • A. Paul Lehr
    Paul Lehr was an American illustrator renowned for his distinctive, visionary science fiction and fantasy book cover art during the mid-20th century.
  • B. Paul Biegler
    Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
  • C. Paul Zimmerer
    Paul Zimmerer was an American entrepreneur best known as the founder of Lindsay Corporation, a major manufacturer of agricultural irrigation and infrastructure equipment.
  • D. Paul Knabenshue
    Paul Knabenshue was an American diplomat best known for serving as the first U.S. Ambassador to Iraq in the early 20th century.
  • E. Paul Weinert
    Paul Weinert was a United States Army soldier and Medal of Honor recipient recognized for his bravery during the Indian Wars.
  • 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: Paul Michels
Triple: [Michels, hasNotableBearer, Paul Michels]
Generated description
Paul Michels is a notable individual recognized for achievements significant enough to be recorded under the surname Michels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paul Michels
Target entity description: Paul Michels is a notable individual recognized for achievements significant enough to be recorded under the surname Michels.
  • A. Paul Lehr
    Paul Lehr was an American illustrator renowned for his distinctive, visionary science fiction and fantasy book cover art during the mid-20th century.
  • B. Paul Biegler
    Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
  • C. Paul Zimmerer
    Paul Zimmerer was an American entrepreneur best known as the founder of Lindsay Corporation, a major manufacturer of agricultural irrigation and infrastructure equipment.
  • D. Paul Knabenshue
    Paul Knabenshue was an American diplomat best known for serving as the first U.S. Ambassador to Iraq in the early 20th century.
  • E. Paul Weinert
    Paul Weinert was a United States Army soldier and Medal of Honor recipient recognized for his bravery during the Indian Wars.
  • 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_69ca8436ba308190903e470776d2d893 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7c94719c81909d7743a57c45e07f completed April 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d20cbe7fb88190a945870540d4c973 completed April 5, 2026, 7:18 a.m.
NEDg Description generation batch_69d20f2aa6588190b842641d41f6179a completed April 5, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_69d20f7c328c8190a58ad56e9e63cba0 completed April 5, 2026, 7:30 a.m.
Created at: March 30, 2026, 7:49 p.m.