Triple

T15311780
Position Surface form Disambiguated ID Type / Status
Subject The Lincoln Lawyer E366054 entity
Predicate cinematographyBy P1953 FINISHED
Object Lukas Ettlin E1173597 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: Lukas Ettlin | Statement: [The Lincoln Lawyer, cinematographyBy, Lukas Ettlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lukas Ettlin
Context triple: [The Lincoln Lawyer, cinematographyBy, Lukas Ettlin]
  • A. Lukas Ettlin chosen
    Lukas Ettlin is a Swiss-born cinematographer and director known for his work on feature films and television series, including action and genre projects.
  • B. Lukas Heller
    Lukas Heller was a German-born British screenwriter best known for his work on psychological thrillers and film adaptations in the 1960s and 1970s.
  • C. Florian Klaempfl
    Florian Klaempfl is a software developer best known as the original creator and lead architect of the Free Pascal compiler.
  • D. Maximilian Bittner
    Maximilian Bittner is a German entrepreneur best known as the founding CEO of Lazada, a major Southeast Asian e-commerce platform.
  • E. Matthias Koenigswieser
    Matthias Koenigswieser is a cinematographer known for his work on feature films such as the live-action Disney movie "Christopher Robin."
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03cd2d5a88190aead748920f93d47 completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff9978ae90819088bf7c8890b7a9a5 completed May 9, 2026, 8:30 p.m.
Created at: April 10, 2026, 3:16 a.m.