Triple

T14309547
Position Surface form Disambiguated ID Type / Status
Subject Maggie Carey E354787 entity
Predicate notableWork P4 FINISHED
Object Funny or Die shorts E76742 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: Funny or Die shorts | Statement: [Maggie Carey, notableWork, Funny or Die shorts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Funny or Die shorts
Context triple: [Maggie Carey, notableWork, Funny or Die shorts]
  • A. Funny or Die chosen
    Funny or Die is a comedy video website and production company known for its celebrity-driven sketches and viral online content.
  • B. Saturday Night Live digital shorts
    Saturday Night Live digital shorts are a series of comedic short films, often musical and absurdist, that became a breakout highlight of SNL in the 2000s and 2010s, popularizing viral sketches like "Lazy Sunday" and "Dick in a Box."
  • C. Shorts
    Shorts is a surname shared by various individuals, including American football player Cecil Shorts III.
  • D. Humor Me
    "Humor Me" is a film edited by Nat Sanders, known for his work on acclaimed independent movies.
  • E. Between Two Ferns
    Between Two Ferns is a satirical online talk show hosted by Zach Galifianakis, known for its awkward, deadpan celebrity interviews and low-budget, mock-public-access style.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b26da48190a96e2f60ace51335 completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d2e2444819090252684673ff3df completed May 8, 2026, 1:32 a.m.
Created at: April 10, 2026, 1:12 a.m.