Triple

T379493
Position Surface form Disambiguated ID Type / Status
Subject Gregory Peck E8645 entity
Predicate child P120 FINISHED
Object Stephen Peck
Stephen Peck is an American advocate for homeless and at-risk veterans who is also known as the son of acclaimed actor Gregory Peck.
 E156765 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: Stephen Peck | Statement: [Gregory Peck, child, Stephen Peck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stephen Peck
Context triple: [Gregory Peck, child, Stephen Peck]
  • A. Jonathan Peck
    Jonathan Peck was one of the sons of acclaimed American actor Gregory Peck.
  • B. Stephen Nicol
    Stephen Nicol is a former Scottish professional footballer and versatile defender best known for his successful spell at Liverpool FC in the 1980s and early 1990s.
  • C. William Nolan
    William Nolan is an editor known for his work on editions of classic adventure literature, including "The Mark of Zorro."
  • D. Paul Webb
    Paul Webb is a screenwriter best known for writing the screenplay for the historical drama film "Selma" (2014), which chronicles a pivotal chapter in the U.S. civil rights movement.
  • E. Steven Pemberton
    Steven Pemberton is a British computer scientist and software engineer known for his work on programming languages, web standards, and contributions to the development of ABC and early Python influences.
  • 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: Stephen Peck
Triple: [Gregory Peck, child, Stephen Peck]
Generated description
Stephen Peck is an American advocate for homeless and at-risk veterans who is also known as the son of acclaimed actor Gregory Peck.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stephen Peck
Target entity description: Stephen Peck is an American advocate for homeless and at-risk veterans who is also known as the son of acclaimed actor Gregory Peck.
  • A. Jonathan Peck chosen
    Jonathan Peck was one of the sons of acclaimed American actor Gregory Peck.
  • B. Stephen Nicol
    Stephen Nicol is a former Scottish professional footballer and versatile defender best known for his successful spell at Liverpool FC in the 1980s and early 1990s.
  • C. William Nolan
    William Nolan is an editor known for his work on editions of classic adventure literature, including "The Mark of Zorro."
  • D. Paul Webb
    Paul Webb is a screenwriter best known for writing the screenplay for the historical drama film "Selma" (2014), which chronicles a pivotal chapter in the U.S. civil rights movement.
  • E. Steven Pemberton
    Steven Pemberton is a British computer scientist and software engineer known for his work on programming languages, web standards, and contributions to the development of ABC and early Python influences.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec2b07248190979229bad3a741c9 completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd4620c7c81909e30a2dfd55602fb completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd72a585c81909343b8ebf8294499 completed March 8, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_69acd7cdafb081908424028e4656c459 completed March 8, 2026, 1:58 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.