Triple

T21113225
Position Surface form Disambiguated ID Type / Status
Subject Beadle Bamford E520222 entity
Predicate associatedWith P37 FINISHED
Object Johanna Barker NE NERFINISHED

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: Johanna Barker | Statement: [Beadle Bamford, associatedWith, Johanna Barker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johanna Barker
Context triple: [Beadle Bamford, associatedWith, Johanna Barker]
  • A. Johanna Barker chosen
    Johanna Barker is the innocent and sheltered daughter of Sweeney Todd in the 2007 film adaptation of the musical thriller, serving as a central figure in the story’s themes of lost family and doomed romance.
  • B. Maria Bicknell
    Maria Bicknell was the wife of English Romantic landscape painter John Constable and a member of a well-connected Suffolk family in early 19th-century England.
  • C. Jean Barker
    Jean Barker is a journalist best known for serving as editor of the publication *The Beachcomber*.
  • D. Frances Barker
    Frances Barker was the wife of William Shirley, the 18th-century British colonial governor of Massachusetts.
  • E. Mary Barstow
    Mary Barstow was the second wife of American illustrator Norman Rockwell and the mother of his three sons.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72103b3888190a19e9a40f01fb439 completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:54 p.m.