Triple

T15732171
Position Surface form Disambiguated ID Type / Status
Subject The Afterparty E381370 entity
Predicate starring P1507 FINISHED
Object Tiffany Haddish E332986 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: Tiffany Haddish | Statement: [The Afterparty, starring, Tiffany Haddish]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiffany Haddish
Context triple: [The Afterparty, starring, Tiffany Haddish]
  • A. Tiffany Haddish chosen
    Tiffany Haddish is an American stand-up comedian and actress known for her breakout role in "Girls Trip" and her energetic, unfiltered comedic style.
  • B. Amber Ruffin
    Amber Ruffin is an American comedian, writer, and television host best known for her work on "Late Night with Seth Meyers" and for creating and starring in "The Amber Ruffin Show."
  • C. Regina Hall
    Regina Hall is an American actress and comedian known for her roles in films such as the Scary Movie series, Girls Trip, and numerous television comedies.
  • D. Leslie Jones
    Leslie Jones is an American film editor known for her work on major Hollywood productions, including the feature film "Starsky & Hutch."
  • E. Leslie Jones
    Leslie Jones is an American comedian and actress known for her work on "Saturday Night Live" and roles in films such as the 2016 "Ghostbusters" reboot.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd3614481908b2694b1d3550058 completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82fed7888190b45f28ac91e0079e completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:46 a.m.