Triple

T3621391
Position Surface form Disambiguated ID Type / Status
Subject Blades of Glory E76734 entity
Predicate editedBy P1954 FINISHED
Object Pamela Martin E458105 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: Pamela Martin | Statement: [Blades of Glory, editedBy, Pamela Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pamela Martin
Context triple: [Blades of Glory, editedBy, Pamela Martin]
  • A. Pamela Martin chosen
    Pamela Martin is an American film editor known for her work on acclaimed movies such as "The Fighter" and "Little Miss Sunshine."
  • B. Pamela Pettler
    Pamela Pettler is an American screenwriter best known for her work on darkly comedic animated films such as "Corpse Bride" and "Monster House."
  • C. Pamela Brown
    Pamela Brown was a British stage and film actress known for her intense character roles in mid-20th-century cinema and theatre.
  • D. Pamela Jones
    Pamela Jones is the fictional, somewhat overbearing but well-meaning mother of Bridget Jones in the "Bridget Jones" novels and film adaptations.
  • E. Pam Ferris
    Pam Ferris is a British actress known for her character roles in film and television, including memorable performances in "Matilda," "Call the Midwife," and "Harry Potter and the Prisoner of Azkaban."
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2b9aa608190a680b250ecf63156 completed March 8, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64b8e4dd88190be82d6e5ad9f2e7a completed March 27, 2026, 9:19 a.m.
Created at: March 8, 2026, 3:23 p.m.