Triple

T10368149
Position Surface form Disambiguated ID Type / Status
Subject Bad Santa E244308 entity
Predicate cinematographyBy P1953 FINISHED
Object Jamie Anderson E528700 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: Jamie Anderson | Statement: [Bad Santa, cinematographyBy, Jamie Anderson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamie Anderson
Context triple: [Bad Santa, cinematographyBy, Jamie Anderson]
  • A. Jamie Anderson
    Jamie Anderson is an American professional snowboarder best known for winning the inaugural women's slopestyle gold medal at the 2014 Winter Olympics.
  • B. Jamie Anderson chosen
    Jamie Anderson is a cinematographer known for her work on feature films, including the romantic comedy "What's Love Got to Do with It?".
  • C. Mikaela Shiffrin
    Mikaela Shiffrin is an American alpine ski racer and multiple Olympic and World Championship gold medalist renowned as one of the most dominant slalom and overall skiers in history.
  • D. Cailey Fleming
    Cailey Fleming is an American actress best known for her role as young Judith Grimes on the television series "The Walking Dead."
  • E. Kimmie Meissner
    Kimmie Meissner is an American figure skater who won the 2006 World Championship and is known for her powerful jumping ability and technical skill.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e97106448190a075948e63184f47 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d79550b2ec8190ada086ddfeb398af completed April 9, 2026, 12:02 p.m.
Created at: April 6, 2026, 12:01 p.m.