Triple

T8917396
Position Surface form Disambiguated ID Type / Status
Subject Santa's workshop E212325 entity
Predicate relatedConcept P37 FINISHED
Object Santa's sleigh E726658 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: Santa's sleigh | Statement: [Santa's workshop, relatedConcept, Santa's sleigh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa's sleigh
Context triple: [Santa's workshop, relatedConcept, Santa's sleigh]
  • A. Santa Claus's sleigh chosen
    Santa Claus's sleigh is the magical, gift-laden vehicle he rides through the sky on Christmas Eve to deliver presents to children around the world.
  • B. Santa Claus's reindeer team
    Santa Claus's reindeer team is the legendary group of flying reindeer that pull Santa's sleigh on Christmas Eve, helping him deliver gifts around the world.
  • C. Blitzen the reindeer
    Blitzen the reindeer is one of Santa Claus’s legendary flying reindeer, traditionally depicted as helping pull Santa’s sleigh on Christmas Eve.
  • D. Dasher
    Dasher is the nickname of Frank "Dasher" Abbandando, a notorious New York mob hitman associated with Murder, Inc. in the mid-20th century.
  • E. Dasher
    Dasher is one of Santa Claus’s traditional flying reindeer, commonly named in the famous Christmas poem “A Visit from St. Nicholas.”
  • 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_69ca8393b1808190bd4336787ffa2c40 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66120eb08190913ab6c42f26ffb8 completed April 1, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba49d65c8190b9d9908822198cc0 completed April 3, 2026, 1:02 p.m.
Created at: March 30, 2026, 6:56 p.m.