Triple

T10554622
Position Surface form Disambiguated ID Type / Status
Subject Christine Diane Teigen E249043 entity
Predicate name P16 FINISHED
Object Christine Diane Teigen E249043 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: Christine Diane Teigen | Statement: [Christine Diane Teigen, name, Christine Diane Teigen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christine Diane Teigen
Context triple: [Christine Diane Teigen, name, Christine Diane Teigen]
  • A. Christine Diane Teigen chosen
    Christine Diane Teigen, known as Chrissy Teigen, is an American model, television personality, and cookbook author prominent for her Sports Illustrated work, social media presence, and lifestyle brand.
  • B. Janet Langhart
    Janet Langhart is an American television journalist, author, and former model known for her work as a news correspondent and for her writings on race and civil rights.
  • C. Elissa Hirsch
    Elissa Hirsch is known as the former wife of American actor Judd Hirsch.
  • D. Sandra Lee
    Sandra Lee is an American television chef and author known for her "Semi-Homemade" cooking concept and numerous Food Network shows.
  • E. Alice Webb
    Alice Webb is a British media executive and producer known for her leadership roles in major broadcasting organizations and involvement in high-profile documentary projects.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d527118da081909ca61bc555a17609 completed April 7, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9346f6a38819087647e7a09f40c41 completed April 10, 2026, 5:33 p.m.
Created at: April 6, 2026, 12:34 p.m.