Triple

T21462653
Position Surface form Disambiguated ID Type / Status
Subject Emma Peel E529510 entity
Predicate spouse P13 FINISHED
Object Peter Peel
Peter Peel is the husband of the fictional British secret agent Emma Peel from the 1960s television series "The Avengers."
 E1486865 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 Peel | Statement: [Emma Peel, spouse, Peter Peel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Peel
Context triple: [Emma Peel, spouse, Peter Peel]
  • A. Bill Peet
    Bill Peet was an American children’s book author and longtime Disney story artist known for his influential work on many classic animated films.
  • B. Paul Peele
    Paul Peele is a notable individual associated with the surname Peele, recognized as a distinguished bearer of that name.
  • C. Peter Pau
    Peter Pau is an acclaimed Hong Kong cinematographer best known internationally for his Oscar-winning work on the film "Crouching Tiger, Hidden Dragon."
  • D. Peter Funt
    Peter Funt is an American television personality and producer best known for hosting and continuing his father Allen Funt’s hidden-camera show "Candid Camera."
  • E. Peter Pilling
    Peter Pilling is a collegiate sports administrator best known for serving as the athletic director at Columbia University, overseeing the Columbia Lions athletic programs.
  • 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 Peel
Triple: [Emma Peel, spouse, Peter Peel]
Generated description
Peter Peel is the husband of the fictional British secret agent Emma Peel from the 1960s television series "The Avengers."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Peel
Target entity description: Peter Peel is the husband of the fictional British secret agent Emma Peel from the 1960s television series "The Avengers."
  • A. Bill Peet
    Bill Peet was an American children’s book author and longtime Disney story artist known for his influential work on many classic animated films.
  • B. Paul Peele
    Paul Peele is a notable individual associated with the surname Peele, recognized as a distinguished bearer of that name.
  • C. Peter Pau
    Peter Pau is an acclaimed Hong Kong cinematographer best known internationally for his Oscar-winning work on the film "Crouching Tiger, Hidden Dragon."
  • D. Peter Funt
    Peter Funt is an American television personality and producer best known for hosting and continuing his father Allen Funt’s hidden-camera show "Candid Camera."
  • E. Peter Pilling
    Peter Pilling is a collegiate sports administrator best known for serving as the athletic director at Columbia University, overseeing the Columbia Lions athletic programs.
  • 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_69e0c458133481908ae8b41a12c4edec completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9efdb188190be79b72e1bd18860 completed April 23, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09cff0982c8190a18afe116e2a0391 completed May 17, 2026, 2:25 p.m.
NEDg Description generation batch_6a09d1c0ba9081909da8754af7e2e33d completed May 17, 2026, 2:33 p.m.
NED2 Entity disambiguation (via description) batch_6a09d271dc948190bde142334bb360ee completed May 17, 2026, 2:36 p.m.
Created at: April 16, 2026, 6:09 p.m.