Triple

T10505864
Position Surface form Disambiguated ID Type / Status
Subject Pierre Berton E247784 entity
Predicate spouse P13 FINISHED
Object Janet Berton
Janet Berton was the wife and long-time partner of Canadian author and historian Pierre Berton, known for supporting his prolific literary career and preserving his legacy.
 E875033 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: Janet Berton | Statement: [Pierre Berton, spouse, Janet Berton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Janet Berton
Context triple: [Pierre Berton, spouse, Janet Berton]
  • A. Lorraine Kirke
    Lorraine Kirke is a British-born New York boutique owner and costume designer known for her bohemian fashion aesthetic and as the mother of actress Jemima Kirke.
  • B. Anne Rennie
    Anne Rennie is known as the wife of bestselling adventure novelist Wilbur Smith.
  • C. Noel Neill
    Noel Neill was an American actress best known for playing Lois Lane in the classic Superman film serials and the 1950s television series "Adventures of Superman."
  • D. Kathryn Erbe
    Kathryn Erbe is an American actress best known for her role as Detective Alexandra Eames on the television series "Law & Order: Criminal Intent."
  • E. Susan Mara
    Susan Mara is a member of the Mara family, the longtime owners of the NFL’s New York Giants franchise.
  • 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: Janet Berton
Triple: [Pierre Berton, spouse, Janet Berton]
Generated description
Janet Berton was the wife and long-time partner of Canadian author and historian Pierre Berton, known for supporting his prolific literary career and preserving his legacy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Janet Berton
Target entity description: Janet Berton was the wife and long-time partner of Canadian author and historian Pierre Berton, known for supporting his prolific literary career and preserving his legacy.
  • A. Lorraine Kirke
    Lorraine Kirke is a British-born New York boutique owner and costume designer known for her bohemian fashion aesthetic and as the mother of actress Jemima Kirke.
  • B. Anne Rennie
    Anne Rennie is known as the wife of bestselling adventure novelist Wilbur Smith.
  • C. Noel Neill
    Noel Neill was an American actress best known for playing Lois Lane in the classic Superman film serials and the 1950s television series "Adventures of Superman."
  • D. Kathryn Erbe
    Kathryn Erbe is an American actress best known for her role as Detective Alexandra Eames on the television series "Law & Order: Criminal Intent."
  • E. Susan Mara
    Susan Mara is a member of the Mara family, the longtime owners of the NFL’s New York Giants franchise.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509a07c908190bf0e3e5d480b306d completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b3d6f6c81908d8247da9d9caab2 completed April 10, 2026, 9:27 p.m.
NEDg Description generation batch_69d96d85f9648190a43c8c924f5139e3 completed April 10, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_69d96e1a36688190b97ced745bc6a30d completed April 10, 2026, 9:39 p.m.
Created at: April 6, 2026, 12:26 p.m.