Triple

T8188266
Position Surface form Disambiguated ID Type / Status
Subject Pepper Teigen E191240 entity
Predicate familyName P18 FINISHED
Object Teigen E191240 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: Teigen | Statement: [Pepper Teigen, familyName, Teigen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teigen
Context triple: [Pepper Teigen, familyName, Teigen]
  • A. Pepper Teigen chosen
    Pepper Teigen is a Thai-American home cook, cookbook author, and television personality best known as Chrissy Teigen’s mother and for popularizing Thai comfort food in the U.S.
  • B. Carey Wilson
    Carey Wilson was an American screenwriter and film producer active during Hollywood's early studio era, known for his work on numerous MGM and RKO pictures.
  • C. Casey Wilson
    Casey Wilson is an American actress, comedian, and screenwriter best known for her work on "Saturday Night Live" and the sitcom "Happy Endings."
  • D. Kimball O'Hara
    Kimball O'Hara is the orphaned Irish-Indian boy and streetwise spy-in-training who serves as the protagonist of Rudyard Kipling’s novel "Kim."
  • E. Kay Nelson
    Kay Nelson was a Hollywood costume designer known for her work on classic films of the 1940s.
  • 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_69ca82c5b6948190a583c096fb0a6c71 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4d9f4a488190b39bdc1792646914 completed March 31, 2026, 4:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc68ea260819094ae0f87abdd8041 completed April 2, 2026, 1:29 a.m.
Created at: March 30, 2026, 5:41 p.m.