Triple

T14434732
Position Surface form Disambiguated ID Type / Status
Subject Makena Lautner E357929 entity
Predicate familyName P18 FINISHED
Object Lautner E355308 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: Lautner | Statement: [Makena Lautner, familyName, Lautner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lautner
Context triple: [Makena Lautner, familyName, Lautner]
  • A. Lautner chosen
    Lautner is a surname most prominently associated with American actor Taylor Lautner, known for his role as Jacob Black in the "Twilight" film series.
  • B. Laudner
    Laudner is a surname most notably associated with former American Major League Baseball catcher Tim Laudner.
  • C. Krier
    Krier is a surname most notably associated with Leon Krier, a Luxembourgish architect and urban planner known for his advocacy of traditional urbanism and criticism of modernist architecture.
  • D. Bohlin
    Bohlin is a Swedish surname associated with various notable individuals in fields such as architecture, sports, and academia.
  • E. Cundey
    Cundey is a surname most notably associated with American cinematographer Dean Cundey, known for his work on influential genre and blockbuster films.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91471a648190adb7b283a6a85c3e completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bd5b1d08190a89e6f004a94b361 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:18 a.m.