Triple

T14462421
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Front E358616 entity
Predicate name P16 FINISHED
Object Rebecca Front E358616 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: Rebecca Front | Statement: [Rebecca Front, name, Rebecca Front]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rebecca Front
Context triple: [Rebecca Front, name, Rebecca Front]
  • A. Rebecca Front chosen
    Rebecca Front is a British actress and comedian best known for her roles in television series such as "The Thick of It," "Lewis," and numerous other UK comedies and dramas.
  • B. Stevie Crawford
    Stevie Crawford is a Scottish former professional footballer and coach best known as a prolific forward in the Scottish leagues and later as a manager.
  • C. Veronica Baker
    Veronica Baker is known as the daughter of Rick Baker, the acclaimed special makeup effects artist and seven-time Academy Award winner.
  • D. Tatia Starkey
    Tatia Starkey is an English bassist and vocalist, known for her work with bands such as Belakiss and for being the granddaughter of Beatles drummer Ringo Starr.
  • E. Karen Morley
    Karen Morley was an American film actress of the 1930s, best known for her roles in pre-Code Hollywood crime dramas and social-themed films.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91ad67bc81908ecdaa7262f6dc55 completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd64973dc08190ab893c95ea3f066c completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:19 a.m.