Triple

T18523183
Position Surface form Disambiguated ID Type / Status
Subject Robert D. Siegel E452641 entity
Predicate directed P7373 FINISHED
Object Big Fan 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: Big Fan | Statement: [Robert D. Siegel, directed, Big Fan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Big Fan
Context triple: [Robert D. Siegel, directed, Big Fan]
  • A. Big Fan chosen
    Big Fan is a dark comedy-drama film about an obsessive New York Giants fan whose life unravels after a violent encounter with his favorite player.
  • B. The Biggest Fan
    The Biggest Fan is a 2002 teen comedy film centered on a high school girl who becomes obsessed with a pop star after he unexpectedly ends up hiding in her bedroom.
  • C. Fan of a Fan
    Fan of a Fan is a collaborative hip hop mixtape by Tyga and Chris Brown that helped boost both artists' profiles with its club-ready tracks and catchy hooks.
  • D. The Fan Club
    The Fan Club is a 1974 thriller novel by Irving Wallace about a group of obsessed fans who kidnap a famous Hollywood actress.
  • E. The Fan
    The Fan is a 1996 psychological thriller film about an obsessive baseball fan whose fixation on his favorite player turns dangerously violent.
  • 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_69d8d387b5548190aa030dad2cb4947e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5338f6da48190bdb374019d10db05 completed April 19, 2026, 7:57 p.m.
Created at: April 10, 2026, 11:37 a.m.