Triple

T8135059
Position Surface form Disambiguated ID Type / Status
Subject Fred Tate E189948 entity
Predicate motherInStory P65999 FINISHED
Object Dede Tate E136936 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: Dede Tate | Statement: [Fred Tate, motherInStory, Dede Tate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dede Tate
Context triple: [Fred Tate, motherInStory, Dede Tate]
  • A. Dede Tate chosen
    Dede Tate is a central character in the film "Little Man Tate," portrayed as the caring but overwhelmed single mother of a child prodigy.
  • B. Dede Robertson
    Dede Robertson was an American nurse, author, and Christian activist best known as a longtime board member of the Christian Broadcasting Network and the wife of televangelist Pat Robertson.
  • C. Dana Dane
    Dana Dane is an American rapper and storyteller known for his humorous narrative style and influential 1980s hip-hop tracks like "Cinderfella Dana Dane."
  • D. Dee Dee
    Dee Dee is Dexter’s exuberant and mischievous older sister in the animated series "Dexter’s Laboratory," known for constantly disrupting his scientific experiments.
  • E. Burny Mattinson
    Burny Mattinson was a veteran Walt Disney animator, director, and story artist whose decades-long career contributed to many classic Disney films.
  • 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_69ca82bcb4848190a9a9d036ad768642 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb43fff6e0819086c95b571272b50c completed March 31, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc949065248190b67ba7aa2688903e completed April 1, 2026, 3:44 a.m.
Created at: March 30, 2026, 5:35 p.m.