Triple

T18099036
Position Surface form Disambiguated ID Type / Status
Subject Schenck E433165 entity
Predicate hasNotableBearer P458 FINISHED
Object Peter Schenck
Peter Schenck is a relatively obscure individual whose primary distinction is sharing a name with the more historically recognized Schenck family line.
 E1395899 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: Peter Schenck | Statement: [Schenck, hasNotableBearer, Peter Schenck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Schenck
Context triple: [Schenck, hasNotableBearer, Peter Schenck]
  • A. Peter Schelshorn
    Peter Schelshorn is a German local politician who serves as the mayor of the town of Schönau im Schwarzwald in Baden-Württemberg.
  • B. Peter Schink
    Peter Schink is a film editor known for his work on the 1996 action film "Barb Wire."
  • C. Peter Schink
    Peter Schink is a screenwriter best known for co-writing the apocalyptic action-horror film "Legion" (2010).
  • D. Peter Schweger
    Peter Schweger is a German architect known for designing prominent contemporary buildings, including major high-rise projects.
  • E. Nicholas Schenck
    Nicholas Schenck was a prominent early 20th-century American film studio executive and theater owner who played a key role in the development of Metro-Goldwyn-Mayer (MGM) and the Hollywood studio system.
  • 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: Peter Schenck
Triple: [Schenck, hasNotableBearer, Peter Schenck]
Generated description
Peter Schenck is a relatively obscure individual whose primary distinction is sharing a name with the more historically recognized Schenck family line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Schenck
Target entity description: Peter Schenck is a relatively obscure individual whose primary distinction is sharing a name with the more historically recognized Schenck family line.
  • A. Peter Schelshorn
    Peter Schelshorn is a German local politician who serves as the mayor of the town of Schönau im Schwarzwald in Baden-Württemberg.
  • B. Peter Schink
    Peter Schink is a film editor known for his work on the 1996 action film "Barb Wire."
  • C. Peter Schink
    Peter Schink is a screenwriter best known for co-writing the apocalyptic action-horror film "Legion" (2010).
  • D. Peter Schweger
    Peter Schweger is a German architect known for designing prominent contemporary buildings, including major high-rise projects.
  • E. Nicholas Schenck
    Nicholas Schenck was a prominent early 20th-century American film studio executive and theater owner who played a key role in the development of Metro-Goldwyn-Mayer (MGM) and the Hollywood studio system.
  • 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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddb521448190b97d2b2aa7e4d7e6 completed April 19, 2026, 1:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07c4dd20d88190bc3dc16062764414 completed May 16, 2026, 1:14 a.m.
NEDg Description generation batch_6a07c5aea8948190b6e5bbcea8053478 completed May 16, 2026, 1:17 a.m.
NED2 Entity disambiguation (via description) batch_6a07c6846fb481908e1d5aae2c53a7ba completed May 16, 2026, 1:21 a.m.
Created at: April 10, 2026, 10:27 a.m.