Triple

T261165
Position Surface form Disambiguated ID Type / Status
Subject Cisco Systems E5543 entity
Predicate hasSubsidiary P254 FINISHED
Object Meraki
Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
 E33847 NE FINISHED

How this triple was built (4 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: Meraki | Statement: [Cisco Systems, hasSubsidiary, Meraki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Meraki
Context triple: [Cisco Systems, hasSubsidiary, Meraki]
  • A. Makers
    Makers is a science fiction novel by Cory Doctorow that explores a near-future maker culture, disruptive innovation, and the social and economic upheavals caused by rapid technological change.
  • B. Soter
    Soter is a Greek term meaning "savior" or "deliverer," often used as a title for deities or revered figures who provide salvation or protection.
  • C. Sloan
    Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
  • D. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • E. Dynamo
    Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Meraki
Triple: [Cisco Systems, hasSubsidiary, Meraki]
Generated description
Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Meraki
Target entity description: Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
  • A. Makers
    Makers is a science fiction novel by Cory Doctorow that explores a near-future maker culture, disruptive innovation, and the social and economic upheavals caused by rapid technological change.
  • B. Soter
    Soter is a Greek term meaning "savior" or "deliverer," often used as a title for deities or revered figures who provide salvation or protection.
  • C. Sloan
    Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
  • D. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • E. Dynamo
    Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
  • F. None of above. chosen

Provenance (5 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d7428dc8190ae12b12a21fcc6cb completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a383773dc481908aeb9eaa09f8467f completed March 1, 2026, 12:08 a.m.
NEDg Description generation batch_69a383fa4f648190b859e0ae0a997f10 completed March 1, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_69a384a01f1c8190bca17608d97413c2 completed March 1, 2026, 12:13 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.