Triple

T15257309
Position Surface form Disambiguated ID Type / Status
Subject Carl Heinrich von Siemens E364679 entity
Predicate affiliation P10 FINISHED
Object Siemens company 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 company | Statement: [Carl Heinrich von Siemens, affiliation, Siemens company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siemens company
Context triple: [Carl Heinrich von Siemens, affiliation, Siemens company]
  • 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 industrial works
    Siemens industrial works is a large industrial complex and manufacturing facility historically developed by Siemens in Berlin’s Siemensstadt district.
  • D. von Siemens
    von Siemens is a prominent German industrial family name most closely associated with the founders and leaders of the Siemens engineering and technology conglomerate.
  • E. Siemens Energy
    Siemens Energy is a global energy technology company specializing in power generation, transmission, and related services for conventional and renewable energy systems.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0084b97908190b3bf7ea7bd75bdc0 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69feef6def4c8190b6aed1f68d336c5a completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:13 a.m.