Triple

T7072834
Position Surface form Disambiguated ID Type / Status
Subject Lionel Jefferson E164740 entity
Predicate motherInLaw P18075 FINISHED
Object Helen Willis E286870 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: Helen Willis | Statement: [Lionel Jefferson, motherInLaw, Helen Willis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen Willis
Context triple: [Lionel Jefferson, motherInLaw, Helen Willis]
  • A. Helen Willis chosen
    Helen Willis is a central character on the sitcom "The Jeffersons," known as Louise Jefferson’s close friend and one half of the show’s groundbreaking interracial couple.
  • B. Helen Wright
    Helen Wright is a wealthy, emotionally volatile socialite who becomes romantically entangled with a young violin prodigy in the film "Humoresque."
  • C. Helen Hughes
    Helen Hughes was a daughter of Charles Evans Hughes, the prominent American statesman who served as both U.S. Secretary of State and Chief Justice of the Supreme Court.
  • D. Helen Marshall
    Helen Marshall is a British academic leader and higher education administrator who has served as Vice-Chancellor of the University of Salford.
  • E. Helen Mack
    Helen Mack was an American film and radio actress of the 1930s and 1940s, known for her versatile performances in both comedy and drama.
  • 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_69c6887b96548190a8a9b3ac8adf4119 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4cb76548190bd98876f8ba925b7 completed March 27, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9061709f48190a9e198dac225aed4 completed March 29, 2026, 10:59 a.m.
Created at: March 27, 2026, 2:39 p.m.