Triple

T3536231
Position Surface form Disambiguated ID Type / Status
Subject Jennifer Aniston E74778 entity
Predicate notableWork P4 FINISHED
Object Cake E251789 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: Cake | Statement: [Jennifer Aniston, notableWork, Cake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cake
Context triple: [Jennifer Aniston, notableWork, Cake]
  • A. Cake chosen
    "Cake" is a 2014 drama film in which Jennifer Aniston stars as a woman struggling with chronic pain and grief, featuring Mamie Gummer in a supporting role.
  • B. Beecake
    Beecake is a Scottish alternative rock band fronted by actor and musician Billy Boyd.
  • C. Pies
    The Pies is a common nickname for the Collingwood Football Club, a prominent Australian rules football team in the Australian Football League.
  • D. Eccles cake
    Eccles cake is a traditional British pastry made of flaky, buttery pastry filled with spiced currants and often enjoyed as a sweet snack or dessert.
  • E. Layer Cake
    Layer Cake is a 2004 British crime thriller film directed by Matthew Vaughn, known for its stylish depiction of London’s criminal underworld and for helping launch Daniel Craig to wider fame.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbcc7b92481908d2d99948780f4d0 completed March 8, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bd237e881909df210a42346b572 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:20 p.m.