Triple

T23560975
Position Surface form Disambiguated ID Type / Status
Subject Grace Adler E579234 entity
Predicate hasFriend P8712 FINISHED
Object Karen Walker 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: Karen Walker | Statement: [Grace Adler, hasFriend, Karen Walker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karen Walker
Context triple: [Grace Adler, hasFriend, Karen Walker]
  • A. Karen Walker chosen
    Karen Walker is a sharp-tongued, fabulously wealthy socialite and assistant known for her outrageous humor and heavy drinking on the sitcom "Will & Grace."
  • B. Karen Walker
    Karen Walker is a former English footballer and prolific striker best known for her long and successful career with Doncaster Belles and the England women's national team.
  • C. Karen Hood
    Karen Hood is the central protagonist of the film "Welcome to L.A.," around whom the story’s interpersonal dramas and emotional developments revolve.
  • D. Nita Talbot
    Nita Talbot is an American actress known for her sharp-witted supporting roles in film and television, including a notable Emmy-nominated performance on the sitcom "Hogan's Heroes."
  • E. Emily Sweeney
    Emily Sweeney is a dermatologist who appears as Rajesh Koothrappali’s love interest on the television sitcom "The Big Bang Theory."
  • 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_69e245fe24588190888f3aec8407d8e3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1af680ee88190a23a6f9fed7ae757 completed April 29, 2026, 7:12 a.m.
Created at: April 17, 2026, 6:16 p.m.