Triple

T8781954
Position Surface form Disambiguated ID Type / Status
Subject Huntington Woods, Michigan E208751 entity
Predicate mayor P185 FINISHED
Object Bob Paul
Bob Paul is a local political figure who has served as the mayor of Huntington Woods, Michigan.
 E756772 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: Bob Paul | Statement: [Huntington Woods, Michigan, mayor, Bob Paul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bob Paul
Context triple: [Huntington Woods, Michigan, mayor, Bob Paul]
  • A. Joseph E. Gibbs
    Joseph E. Gibbs is an American businessman best known as a co-founder of the Golf Channel, a cable network dedicated to golf coverage and programming.
  • B. John Sparks
    John Sparks was a 19th-century American politician who served as the 10th Governor of Nevada.
  • C. Homer Brightman
    Homer Brightman was an American screenwriter best known for his work on classic Disney animated films, including contributing to the screenplay of the 1950 feature "Cinderella."
  • D. Carl Schenkel
    Carl Schenkel was a Swiss film director known for his work on thrillers and adventure films in both European and Hollywood cinema.
  • E. Joseph Swing
    Joseph Swing was a U.S. Army general and later Commissioner of the Immigration and Naturalization Service, best known for directing large-scale immigration enforcement efforts in the 1950s.
  • 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: Bob Paul
Triple: [Huntington Woods, Michigan, mayor, Bob Paul]
Generated description
Bob Paul is a local political figure who has served as the mayor of Huntington Woods, Michigan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bob Paul
Target entity description: Bob Paul is a local political figure who has served as the mayor of Huntington Woods, Michigan.
  • A. Joseph E. Gibbs
    Joseph E. Gibbs is an American businessman best known as a co-founder of the Golf Channel, a cable network dedicated to golf coverage and programming.
  • B. John Sparks
    John Sparks was a 19th-century American politician who served as the 10th Governor of Nevada.
  • C. Homer Brightman
    Homer Brightman was an American screenwriter best known for his work on classic Disney animated films, including contributing to the screenplay of the 1950 feature "Cinderella."
  • D. Carl Schenkel
    Carl Schenkel was a Swiss film director known for his work on thrillers and adventure films in both European and Hollywood cinema.
  • E. Joseph Swing
    Joseph Swing was a U.S. Army general and later Commissioner of the Immigration and Naturalization Service, best known for directing large-scale immigration enforcement efforts in the 1950s.
  • 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_69ca835fbee88190bf625939bac48d7f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f7155b081908891e84b704f0ebf completed March 31, 2026, 11:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51e9d97c8190a947848fdaa5b67d completed April 3, 2026, 5:36 a.m.
NEDg Description generation batch_69cf5323b7c08190819de236e01ce9d3 completed April 3, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_69cf54a056408190bd536f79e3ec33be completed April 3, 2026, 5:48 a.m.
Created at: March 30, 2026, 6:42 p.m.