Triple

T5293939
Position Surface form Disambiguated ID Type / Status
Subject Blade Runner 2049 E119808 entity
Predicate castMember P1668 FINISHED
Object Mackenzie Davis E226452 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: Mackenzie Davis | Statement: [Blade Runner 2049, castMember, Mackenzie Davis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mackenzie Davis
Context triple: [Blade Runner 2049, castMember, Mackenzie Davis]
  • A. Mackenzie Davis chosen
    Mackenzie Davis is a Canadian actress known for her roles in films like "Blade Runner 2049" and "The Martian" and the TV series "Halt and Catch Fire."
  • B. MacKenzie Porter
    MacKenzie Porter is a Canadian actress and country music singer known for her roles in television series and her successful recording career.
  • C. Dichen Lachman
    Dichen Lachman is a Nepalese-Australian actress and producer best known for her genre television roles in series such as Dollhouse, Agents of S.H.I.E.L.D., and The 100.
  • D. Makena Lautner
    Makena Lautner is the younger sister of American actor Taylor Lautner, known for maintaining a relatively private life outside of her brother’s fame.
  • E. Suki Waterhouse
    Suki Waterhouse is an English model, actress, and singer known for her fashion work, film roles, and music career.
  • 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_69bd446f22b88190b6a47fb91c68a3e7 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84f034f081908027a43120b6e122 completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06f74a608190bdd52c75777dba5d completed March 21, 2026, 9 p.m.
Created at: March 20, 2026, 1:52 p.m.