Triple

T12369683
Position Surface form Disambiguated ID Type / Status
Subject Thomas Mann E294967 entity
Predicate actedIn P1668 FINISHED
Object Fun Size E488401 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: Fun Size | Statement: [Thomas Mann, actedIn, Fun Size]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fun Size
Context triple: [Thomas Mann, actedIn, Fun Size]
  • A. Fun Size chosen
    Fun Size is a 2012 teen comedy film produced by Nickelodeon Movies that follows a Halloween night gone wrong when a high school girl loses track of her little brother.
  • B. Life-Size
    Life-Size is a 2000 fantasy-comedy television film in which a young girl accidentally brings her fashion doll to life, starring Tyra Banks as the doll and Lindsay Lohan as the girl.
  • C. Tiny
    Tiny was the ironic nickname of Bernard Freyberg, a highly decorated British-New Zealand military commander and World War II general.
  • D. Tiny
    Tiny is the giant blue ox companion of the legendary lumberjack Paul Bunyan in American folklore.
  • E. Mini
    Mini is a young Bengali girl in Rabindranath Tagore’s short story "Kabuliwala," whose innocent friendship with an Afghan fruit seller forms the emotional core of the narrative.
  • 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93fa65a608190a1597a49751185a8 completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62abdad1c8190b083791d60138f2a completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:54 p.m.