Triple

T20269717
Position Surface form Disambiguated ID Type / Status
Subject Winnie Holzman E499061 entity
Predicate coCreatedTelevisionSeries P58014 FINISHED
Object Huge NE NERFINISHED

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: Huge | Statement: [Winnie Holzman, coCreatedTelevisionSeries, Huge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huge
Context triple: [Winnie Holzman, coCreatedTelevisionSeries, Huge]
  • A. Huge chosen
    Huge is a teen drama television series centered on a group of overweight campers at a weight-loss camp, known for its exploration of body image and self-acceptance.
  • B. Gigantic
    "Gigantic" is an alternative rock song by the Pixies, notable for its prominent bassline and Kim Deal's lead vocals.
  • C. Gigantic
    Gigantic is a 2008 indie romantic comedy film starring Paul Dano as a mattress salesman who pursues international adoption while navigating an unconventional relationship.
  • D. Groß
    Groß is a German surname most notably borne by the influential Dadaist and New Objectivity painter and caricaturist George Grosz.
  • E. Big
    Big is a 1988 fantasy-comedy film in which Tom Hanks plays a boy who magically becomes an adult overnight, earning widespread acclaim and helping establish him as a major Hollywood star.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e675dc8e708190b840d687f134c9e8 completed April 20, 2026, 6:52 p.m.
Created at: April 11, 2026, 11:42 p.m.