Triple

T3854941
Position Surface form Disambiguated ID Type / Status
Subject Lady in the Water E89989 entity
Predicate castMember P1668 FINISHED
Object Cindy Cheung E268524 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: Cindy Cheung | Statement: [Lady in the Water, castMember, Cindy Cheung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cindy Cheung
Context triple: [Lady in the Water, castMember, Cindy Cheung]
  • A. Cindy Cheung chosen
    Cindy Cheung is an American actress known for her work in independent films and television, often appearing in character-driven dramas and comedies.
  • B. Vivian Chan
    Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
  • C. Melissa Chiu
    Melissa Chiu is an Australian-born art historian and curator known for her leadership roles in major contemporary art institutions, including directing the Hirshhorn Museum and Sculpture Garden in Washington, D.C.
  • D. Yvonne Szeto
    Yvonne Szeto is a prominent architect and partner at the international architecture firm Pei Cobb Freed & Partners, known for her work on major cultural and institutional projects.
  • E. Leslie Chow
    Leslie Chow is a wildly eccentric, foul-mouthed, and unpredictable gangster character from The Hangover film series, known for his outrageous antics and chaotic energy.
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec05ec4c8190bd5e5463163712dc completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51231608c8190bbc5dc990fba1606 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:19 p.m.