Triple

T10752286
Position Surface form Disambiguated ID Type / Status
Subject Case 39 E253598 entity
Predicate starring P1507 FINISHED
Object Cynthia Stevenson E235554 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: Cynthia Stevenson | Statement: [Case 39, starring, Cynthia Stevenson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cynthia Stevenson
Context triple: [Case 39, starring, Cynthia Stevenson]
  • A. Cynthia Stevenson chosen
    Cynthia Stevenson is an American actress known for her work in film and television, including roles in projects like "Home for the Holidays" and the series "Dead Like Me."
  • B. Cynthia Solomon
    Cynthia Solomon is a pioneering computer scientist and educator best known for her foundational work in the development of educational programming languages for children, including co-creating Logo.
  • C. Cynthia Stone
    Cynthia Stone was an American actress best known for her work in early television and for her marriage to actor Jack Lemmon.
  • D. Cynthia Potter
    Cynthia Potter is a fictional character appearing in the classic 1938 Mickey Rooney film "Love Finds Andy Hardy."
  • E. Cynthia Blaise
    Cynthia Blaise is an American dialect coach and actress known for her work on films such as "Bad Teacher" and "The Tiger Hunter."
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d71dc184d0819085f8bc4edb034377 completed April 9, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69f739644ed48190896d7b2b6c3b5f8f completed May 3, 2026, 12:02 p.m.
Created at: April 8, 2026, 9:15 p.m.