Triple

T13881414
Position Surface form Disambiguated ID Type / Status
Subject Carrie Pipperidge E333725 entity
Predicate singsSong P12693 FINISHED
Object Mister Snow E333721 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: Mister Snow | Statement: [Carrie Pipperidge, singsSong, Mister Snow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mister Snow
Context triple: [Carrie Pipperidge, singsSong, Mister Snow]
  • A. Mister Snow chosen
    "Mister Snow" is a romantic character song from Rodgers and Hammerstein's classic musical "Carousel," sung by the heroine as she imagines a future with her suitor, Enoch Snow.
  • B. Snow Miser
    Snow Miser is a comically villainous, cold-loving winter spirit from the Rankin/Bass Christmas specials, best known for controlling snow and ice and singing about his frosty powers.
  • C. The Mister
    The Mister is a contemporary romance novel by E. L. James, known for its Cinderella-style love story and for being her follow-up to the Fifty Shades series.
  • D. Jack Snow
    Jack Snow was an American writer best known for continuing L. Frank Baum’s Oz series with additional novels and stories.
  • E. Snowman
    Snowman is the post-apocalyptic survivor and narrator of Margaret Atwood’s dystopian novel "Oryx and Crake," through whose perspective the story’s ruined world and its origins are revealed.
  • 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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be8566881908b8902e3cd567669 completed April 14, 2026, 9:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c711f9b08190aa5981320597e83b completed May 3, 2026, 10:07 p.m.
Created at: April 9, 2026, 10:15 p.m.