Triple

T16008149
Position Surface form Disambiguated ID Type / Status
Subject Maggie Q E388270 entity
Predicate stageName P7872 FINISHED
Object Maggie Q E388270 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: Maggie Q | Statement: [Maggie Q, stageName, Maggie Q]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maggie Q
Context triple: [Maggie Q, stageName, Maggie Q]
  • A. Maggie Q chosen
    Maggie Q is an American actress and model best known for her action roles in films like the Mission: Impossible franchise and the TV series Nikita and Designated Survivor.
  • B. Nina Sharp
    Nina Sharp is a high-ranking executive at Massive Dynamic and a key figure in the science-fiction TV series "Fringe," known for her complex moral ambiguity and deep involvement in the show's fringe science conspiracies.
  • C. Jessica Lu
    Jessica Lu is an American actress best known for her television roles, including a main role on the sci-fi drama series "Reverie."
  • D. Maya Van Dien
    Maya Van Dien is the daughter of American actress Catherine Oxenberg and actor Casper Van Dien.
  • E. Lisa Lu
    Lisa Lu is a Chinese-American actress known for her distinguished film and television career spanning both Hollywood and Chinese cinema, including a prominent role in "Crazy Rich Asians."
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15800e3608190bd3e1123ccc6c326 completed April 16, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf22db3481909141ddef151d0341 completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 4:55 a.m.