Triple

T9447393
Position Surface form Disambiguated ID Type / Status
Subject Terminator: Dark Fate E227797 entity
Predicate starring P1507 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: [Terminator: Dark Fate, starring, Mackenzie Davis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mackenzie Davis
Context triple: [Terminator: Dark Fate, starring, 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_69ca8439f8bc8190997f2ef40c9f0bc2 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f35394c8190aa77528dabd6139c completed April 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1106aeb708190bbbe1d05b7472194 completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:51 p.m.