Triple

T17506558
Position Surface form Disambiguated ID Type / Status
Subject Penner E426331 entity
Predicate usedBy P260 FINISHED
Object Solomon Penner
Solomon Penner is an individual known primarily in relation to the use or association with the name or term "Penner."
E1277382 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: Solomon Penner | Statement: [Penner, usedBy, Solomon Penner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Solomon Penner
Context triple: [Penner, usedBy, Solomon Penner]
  • A. David B. Culberson
    David B. Culberson was a 19th-century American politician and Confederate officer from Texas who served in the U.S. House of Representatives and for whom Culberson County, Texas, is named.
  • B. Ralph Penner
    Ralph Penner is an individual associated with or identified by the name "Penner," though no widely known public information further distinguishes him.
  • C. Erdman Penner
    Erdman Penner was a Canadian-born screenwriter and story artist best known for his work on classic Walt Disney animated films in the mid-20th century.
  • D. Richard Berkling
    Richard Berkling is a Swedish sports executive best known for serving as chairman of the football club IFK Göteborg.
  • E. Andrew P. Solt
    Andrew P. Solt was a mid-20th-century American screenwriter best known for his work in film noir and dramatic cinema.
  • 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: Solomon Penner
Triple: [Penner, usedBy, Solomon Penner]
Generated description
Solomon Penner is an individual known primarily in relation to the use or association with the name or term "Penner."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Solomon Penner
Target entity description: Solomon Penner is an individual known primarily in relation to the use or association with the name or term "Penner."
  • A. David B. Culberson
    David B. Culberson was a 19th-century American politician and Confederate officer from Texas who served in the U.S. House of Representatives and for whom Culberson County, Texas, is named.
  • B. Ralph Penner chosen
    Ralph Penner is an individual associated with or identified by the name "Penner," though no widely known public information further distinguishes him.
  • C. Erdman Penner
    Erdman Penner was a Canadian-born screenwriter and story artist best known for his work on classic Walt Disney animated films in the mid-20th century.
  • D. Richard Berkling
    Richard Berkling is a Swedish sports executive best known for serving as chairman of the football club IFK Göteborg.
  • E. Andrew P. Solt
    Andrew P. Solt was a mid-20th-century American screenwriter best known for his work in film noir and dramatic cinema.
  • F. None of above.

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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45258b73c81909db581d4f1d27921 completed April 19, 2026, 3:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01e80a961c8190b167076aa89bf8a1 completed May 11, 2026, 2:30 p.m.
NEDg Description generation batch_6a01f08c56cc81909822635127254ef1 completed May 11, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_6a01f0ebf9e4819091d1b59964c6a275 completed May 11, 2026, 3:08 p.m.
Created at: April 10, 2026, 5:48 a.m.