Triple

T12295189
Position Surface form Disambiguated ID Type / Status
Subject Mark Fergus E293064 entity
Predicate workedOn P3 FINISHED
Object First Snow E975310 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: First Snow | Statement: [Mark Fergus, workedOn, First Snow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: First Snow
Context triple: [Mark Fergus, workedOn, First Snow]
  • A. First Snow chosen
    First Snow is a 2006 psychological thriller film about a salesman whose life unravels after a fortune teller predicts his imminent death.
  • B. Snowfall
    Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
  • C. Snow Wonder
    Snow Wonder is a 2005 made-for-television holiday drama film that intertwines multiple characters' lives during a Christmas Eve snowstorm.
  • D. Thunder Snow
    Thunder Snow is a prominent Irish-bred Thoroughbred racehorse best known for winning back-to-back Dubai World Cups in 2018 and 2019.
  • E. Rooftops in the Snow
    "Rooftops in the Snow" is an 1878 Impressionist painting by Gustave Caillebotte depicting Parisian rooftops blanketed in snow with a strikingly modern, atmospheric realism.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93ed7251c8190b94d7cd75ad49b9c completed April 10, 2026, 6:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a995c508190b7ef77e400d03f87 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:52 p.m.