Triple

T14080649
Position Surface form Disambiguated ID Type / Status
Subject David Arquette E338855 entity
Predicate spouse P13 FINISHED
Object Courteney Cox E330421 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: Courteney Cox | Statement: [David Arquette, spouse, Courteney Cox]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Courteney Cox
Context triple: [David Arquette, spouse, Courteney Cox]
  • A. Courteney Cox chosen
    Courteney Cox is an American actress best known for playing Monica Geller on the hit television sitcom "Friends."
  • B. Shelley Long
    Shelley Long is an American actress best known for her Emmy-winning role as Diane Chambers on the television sitcom "Cheers."
  • C. Kirstie Alley
    Kirstie Alley was an American actress best known for her Emmy-winning role as Rebecca Howe on the hit sitcom "Cheers" and for her work in films like "Look Who's Talking."
  • D. Laraine Newman
    Laraine Newman is an American comedian and actress best known as one of the original cast members of Saturday Night Live in the 1970s.
  • E. Megan Mullally
    Megan Mullally is an American actress, comedian, and singer best known for her Emmy-winning role as Karen Walker on the television sitcom "Will & Grace."
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5c5f759c81909bfd60ab35b0937b completed April 14, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd1930da6481908d17adc6f7bbedd4 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:21 p.m.