Triple

T15400767
Position Surface form Disambiguated ID Type / Status
Subject Jack Tripper E368307 entity
Predicate roommateOf P29563 FINISHED
Object Cindy Snow E998526 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: Cindy Snow | Statement: [Jack Tripper, roommateOf, Cindy Snow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cindy Snow
Context triple: [Jack Tripper, roommateOf, Cindy Snow]
  • A. Cindy Snow chosen
    Cindy Snow is a bubbly, somewhat naive nurse who serves as one of the central roommates on the classic American sitcom "Three's Company."
  • B. Tina Snow
    Tina Snow is an alter ego and early mixtape title of American rapper Megan Thee Stallion, embodying her confident, hardcore Southern rap persona.
  • C. Cindy Green
    Cindy Green is a central character in the fantasy drama film "The Odd Life of Timothy Green," portrayed as a hopeful, loving woman who longs to become a mother.
  • D. Cindy Morgan
    Cindy Morgan is an American actress best known for her roles in the comedy film "Caddyshack" and the science fiction film "Tron."
  • E. Cindy Holland
    Cindy Holland is a television executive best known for her influential role in developing and overseeing original content at Netflix.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8d89e08190b7cae778d89fb5e1 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff13567e3481908eb6293c6af35f3a completed May 9, 2026, 10:58 a.m.
Created at: April 10, 2026, 3:19 a.m.