Triple

T10588741
Position Surface form Disambiguated ID Type / Status
Subject The White Lotus E249925 entity
Predicate starred P5563 FINISHED
Object Connie Britton E248789 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: Connie Britton | Statement: [The White Lotus, starred, Connie Britton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Connie Britton
Context triple: [The White Lotus, starred, Connie Britton]
  • A. Connie Britton chosen
    Connie Britton is an American actress best known for her roles in television series such as "Friday Night Lights," "Nashville," and "The White Lotus."
  • B. Angie Harmon
    Angie Harmon is an American actress and former model best known for her starring role as detective Jane Rizzoli on the television series "Rizzoli & Isles."
  • C. Elizabeth Gilliland
    Elizabeth Gilliland was a woman after whom the town of Elizabethtown in New York was named, likely an early settler or figure of local historical significance.
  • D. Melissa Cobb
    Melissa Cobb is an American film producer best known for her work on major animated features, including the Kung Fu Panda franchise.
  • E. Lynn Collins
    Lynn Collins is an American actress known for her roles in films such as X-Men Origins: Wolverine and John Carter, as well as various television series.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d527793c588190bfe3a5261eb7f919 completed April 7, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b9440548190bff01847a940266b completed April 10, 2026, 7:12 p.m.
Created at: April 6, 2026, 12:40 p.m.