Triple

T22256441
Position Surface form Disambiguated ID Type / Status
Subject Foals – What Went Down (production) E550105 entity
Predicate recordingEngineer P60232 FINISHED
Object Catherine Marks 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: Catherine Marks | Statement: [Foals – What Went Down (production), recordingEngineer, Catherine Marks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catherine Marks
Context triple: [Foals – What Went Down (production), recordingEngineer, Catherine Marks]
  • A. Catherine Marks chosen
    Catherine Marks is an acclaimed Australian record producer and audio engineer known for her work with prominent rock and alternative artists.
  • B. Catherine Wells
    Catherine Wells is known as the wife of Canadian actor Henry Czerny, recognized for his roles in film and television such as the Mission: Impossible series.
  • C. Catherine Moses
    Catherine Moses was the sister of famed American sharpshooter and exhibition shooter Annie Oakley.
  • D. Catherine Matthews
    Catherine Matthews is a person notable enough to be recognized as a significant bearer of the surname Matthews.
  • E. Catherine Schneider
    Catherine Schneider is known as a former spouse of French film director and screenwriter Roger Vadim.
  • 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_69e11e42adb8819087714772ea606709 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f138c314308190a5eea84e1750158a completed April 28, 2026, 10:46 p.m.
Created at: April 16, 2026, 8:39 p.m.