Triple

T12780086
Position Surface form Disambiguated ID Type / Status
Subject Karen Blanche Ziegler E305483 entity
Predicate spouse P13 FINISHED
Object Robert Burton E513723 NE FINISHED

How this triple was built (2 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: Robert Burton | Statement: [Karen Blanche Ziegler, spouse, Robert Burton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Robert Burton
Context triple: [Karen Blanche Ziegler, spouse, Robert Burton]
  • A. Robert Burton chosen
    Robert Burton was an American character actor active in mid-20th-century film and television, often appearing in supporting roles.
  • B. John Camden Hotten
    John Camden Hotten was a 19th-century English publisher, bookseller, and author known for his influential role in Victorian literary culture and for founding the firm that became Chatto & Windus.
  • C. Henry Fowler
    Henry Fowler was a prominent British railway engineer best known for designing influential steam locomotives in the early 20th century.
  • D. John Warburton
    John Warburton was a British-born actor known for his supporting roles in Hollywood films during the 1930s and 1940s.
  • E. John Warburton
    John Warburton was an 18th-century English antiquary and collector known for preserving and cataloguing rare manuscripts and historical documents.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e5a5680819095dcd491486d23e7 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f685030cbc8190856bf5254e231d25 completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:29 p.m.