Triple

T5039631
Position Surface form Disambiguated ID Type / Status
Subject MTV Films E113511 entity
Predicate notableWork P4 FINISHED
Object Pootie Tang E374577 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: Pootie Tang | Statement: [MTV Films, notableWork, Pootie Tang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pootie Tang
Context triple: [MTV Films, notableWork, Pootie Tang]
  • A. Pootie Tang chosen
    Pootie Tang is a 2001 satirical comedy film, based on a sketch from The Chris Rock Show, about a cool, nonsensical hero who battles corporate exploitation of inner-city youth.
  • B. Sam Poo Kong
    Sam Poo Kong is a historic Chinese temple complex in Semarang, Indonesia, revered as a cultural and religious site linked to the legendary admiral Zheng He.
  • C. Paulie Bleeker
    Paulie Bleeker is a shy, sweet-natured high school track athlete and the awkward love interest of the title character in the film "Juno."
  • D. Pogo Poole
    Pogo Poole is the charming, witty, and free-spirited protagonist of the play and film "The Pleasure of His Company," known for disrupting his daughter's orderly life when he reenters her world.
  • E. Magoo
    Magoo was an American rapper best known as one half of the hip hop duo Timbaland & Magoo, active in the late 1990s and early 2000s.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73dbf00c819094b67809dafdecc6 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c8084388190b25bbffc42f0b3ed completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:37 p.m.