Triple

T37968608
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen de México plant E947215 entity
Predicate hasSecondaryLanguageOfWork P9103 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: [Volkswagen de México plant, hasSecondaryLanguageOfWork, German]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSecondaryLanguageOfWork
Context triple: [Volkswagen de México plant, hasSecondaryLanguageOfWork, German]
  • A. hasSecondaryLanguage chosen
    Indicates that an entity possesses or uses a secondary language in addition to its primary language.
  • B. hasSecondaryNationalLanguage
    Indicates that an entity possesses an officially recognized secondary national language in addition to its primary national language.
  • C. hasSecondaryLanguageFamily
    Indicates that an entity has an additional, non-primary association with a particular language family.
  • D. hasSecondaryLanguageNearby
    Indicates that an entity has at least one secondary language present or used in its immediate vicinity or surrounding context.
  • E. hasSecondaryLanguageTradition
    Indicates that an entity possesses an additional, non-primary language tradition associated with it, such as in its use, documentation, or cultural context.
  • 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_69f76ef7062c819091bfacb7e83aa1e0 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_6a00b3d2e0c88190a8bf49576e654f64 completed May 10, 2026, 4:35 p.m.
PD Predicate disambiguation batch_6a00b376f4e48190a6676779fe02ea9f completed May 10, 2026, 4:33 p.m.
Created at: May 3, 2026, 4:20 p.m.