Triple

T32286422
Position Surface form Disambiguated ID Type / Status
Subject Oskar Werner as Jules E824841 entity
Predicate performanceLanguageSecondary P43093 FINISHED
Object German LITERAL 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: German | Statement: [Oskar Werner as Jules, performanceLanguageSecondary, German]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: performanceLanguageSecondary
Context triple: [Oskar Werner as Jules, performanceLanguageSecondary, German]
  • A. hasSecondaryLanguage
    Indicates that an entity possesses or uses a secondary language in addition to its primary language.
  • B. performedLanguage chosen
    Indicates that an action, work, or performance was carried out using a specified language.
  • C. secondaryLanguageSupport
    Indicates that an entity provides assistance, services, or functionality in an additional (non-primary) language.
  • D. primaryLanguageSide2
    Indicates that the second entity in the relationship uses or is associated with the primary language specified.
  • E. suffixLanguage
    Indicates that one language is used as a suffix or ending element in the formation or representation of another language or linguistic expression.
  • F. None of above.

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_69f349101b788190b4f14884dc7d1ed2 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69fddf721c1481909301a0f379368f10 completed May 8, 2026, 1:04 p.m.
PD Predicate disambiguation batch_69fddda1ae7c8190b5848ff9a9e39826 completed May 8, 2026, 12:57 p.m.
Created at: May 1, 2026, 12:43 a.m.