Triple

T19440036
Position Surface form Disambiguated ID Type / Status
Subject Rachel Ferrier E486324 entity
Predicate hasGuardian P28704 FINISHED
Object Ray Ferrier 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: Ray Ferrier | Statement: [Rachel Ferrier, hasGuardian, Ray Ferrier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray Ferrier
Context triple: [Rachel Ferrier, hasGuardian, Ray Ferrier]
  • A. Ray Ferrier chosen
    Ray Ferrier is the blue-collar New Jersey dockworker and struggling divorced father who becomes the central protagonist fighting to protect his children during the alien invasion in the 2005 film "War of the Worlds."
  • B. James Naughtie
    James Naughtie is a Scottish broadcaster and journalist best known as a long-serving presenter of BBC Radio 4’s flagship news programme, Today.
  • C. James Frith
    James Frith is a British Labour Party politician who served as the Member of Parliament for the constituency of Bury North.
  • D. Martyn Fleming
    Martyn Fleming is a fictional character from the 1992 British romantic drama film "Damage," directed by Louis Malle and based on Josephine Hart's novel.
  • E. Roger Broggie
    Roger Broggie was a pioneering Disney Imagineer and master machinist who played a crucial role in developing many of Walt Disney’s early technical innovations and theme park attractions.
  • 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63364371081908e899c2a47af4e5d completed April 20, 2026, 2:08 p.m.
Created at: April 10, 2026, 1:38 p.m.