Triple

T10349601
Position Surface form Disambiguated ID Type / Status
Subject Penelope Wilton E243843 entity
Predicate spouse P13 FINISHED
Object Daniel Massey E695678 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: Daniel Massey | Statement: [Penelope Wilton, spouse, Daniel Massey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Massey
Context triple: [Penelope Wilton, spouse, Daniel Massey]
  • A. Daniel Massey chosen
    Daniel Massey was a British actor known for his work in film, television, and theatre, and for being part of the prominent Massey acting family.
  • B. James Massey
    James Massey was an American information theorist and cryptographer known for his influential contributions to coding theory and cryptographic algorithms.
  • C. Geoffrey Sax
    Geoffrey Sax is a British film and television director known for his work on dramas and genre series, including projects like the U.S. adaptation of "Getting On."
  • D. Jamie Massey
    Jamie Massey is a character in the film "While We're Young," appearing as part of the story’s ensemble of relationships and generational contrasts.
  • E. Sam Barrington
    Sam Barrington is an American former NFL linebacker who played primarily for the Green Bay Packers after a standout college career at the University of South Florida.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e946cbb881909b88536d0107995d completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f53484881909fb976efb3882b9b completed April 10, 2026, 6:57 a.m.
Created at: April 6, 2026, 11:57 a.m.