Triple

T1903774
Position Surface form Disambiguated ID Type / Status
Subject VWAG E37751 entity
Predicate underlyingCompanyHeadquartersLocation P22347 FINISHED
Object Wolfsburg, Germany E74139 NE FINISHED

How this triple was built (3 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: Wolfsburg, Germany | Statement: [VWAG, underlyingCompanyHeadquartersLocation, Wolfsburg, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolfsburg, Germany
Context triple: [VWAG, underlyingCompanyHeadquartersLocation, Wolfsburg, Germany]
  • A. Wolfsburg chosen
    Wolfsburg is a German city best known as the headquarters and main production site of the Volkswagen automobile company.
  • B. Brunswick, Germany
    Brunswick, Germany is a historic city in Lower Saxony known for its medieval architecture, former status as a ducal residence, and role as an important commercial and cultural center in northern Germany.
  • C. Krefeld, Germany
    Krefeld, Germany is an industrial city in North Rhine-Westphalia known historically for its textile and silk production.
  • D. Hamm, Germany
    Hamm is a city in the German state of North Rhine-Westphalia, known as an industrial and transportation hub in the eastern Ruhr area.
  • E. Weinheim, Germany
    Weinheim, Germany is a town in the state of Baden-Württemberg known for its historic old town, twin castles, and role as a regional economic and publishing center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: underlyingCompanyHeadquartersLocation
Context triple: [VWAG, underlyingCompanyHeadquartersLocation, Wolfsburg, Germany]
  • A. employerHeadquarters
    Indicates the location where an employer’s main corporate offices or central administrative operations are based.
  • B. headquartersLocation
    Indicates the place where an organization’s main administrative center or principal office is located.
  • C. locationOfUnderlyingCompany chosen
    Indicates the geographic place where the underlying company is based, registered, or operates.
  • D. majorCompanyHeadquartered
    Indicates that a company is a primary or significant corporate entity whose main headquarters is located in a specified place.
  • E. hasParentCompanyHeadquarters
    Indicates that a company’s parent organization has its main headquarters located at a specified place.
  • F. None of above.

Provenance (4 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb34d94fc8190a5bf1e582c77c725 completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3d0d01c8190ae0c8029fead4008 completed March 8, 2026, 10:10 p.m.
PD Predicate disambiguation batch_69abafe9f8b0819086d8f6288511c66d completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:35 p.m.