Triple

T3480901
Position Surface form Disambiguated ID Type / Status
Subject Werner von Siemens E73486 entity
Predicate founded P104 FINISHED
Object Siemens AG E49800 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: Siemens AG | Statement: [Werner von Siemens, founded, Siemens AG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siemens AG
Context triple: [Werner von Siemens, founded, Siemens AG]
  • A. Siemens chosen
    Siemens is a major German multinational conglomerate best known for its leading roles in industrial manufacturing, energy, healthcare technology, and infrastructure solutions worldwide.
  • B. S7 Group
    S7 Group is a Russian aviation holding company best known for owning and operating S7 Airlines and related air transport businesses.
  • C. Siemens Energy
    Siemens Energy is a global energy technology company specializing in power generation, transmission, and related services for conventional and renewable energy systems.
  • D. Siemens Avanto
    Siemens Avanto is a family of light rail and tram-train vehicles developed by Siemens for urban and regional public transport systems.
  • E. Bosch
    Bosch is a multinational engineering and technology company best known for its automotive components, industrial products, and household appliances.
  • 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_69ad85b3c9b08190857cae74c7f36da9 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb75850c8190ad02cf2bde8be8a7 completed March 8, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373b5086081908ee4491860597557 completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:17 p.m.