Triple

T1503507
Position Surface form Disambiguated ID Type / Status
Subject Meraki E33847 entity
Predicate brand P1500 FINISHED
Object Cisco Meraki E33846 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: Cisco Meraki | Statement: [Meraki, brand, Cisco Meraki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cisco Meraki
Context triple: [Meraki, brand, Cisco Meraki]
  • A. Cisco Meraki chosen
    Cisco Meraki is a cloud-managed IT platform that provides centralized management for wireless, switching, security, and other network devices.
  • B. Juniper Networks
    Juniper Networks is a multinational networking and cybersecurity company known for its high-performance routers, switches, and related infrastructure solutions for service providers and enterprises.
  • C. Cisco Systems
    Cisco Systems is a multinational technology conglomerate best known for designing and selling networking hardware, software, and telecommunications equipment used worldwide.
  • D. Cisco Nexus switches
    Cisco Nexus switches are a family of high-performance, data center–class network switches designed by Cisco Systems for scalable, low-latency, and highly virtualized environments.
  • E. Opsware
    Opsware was a data center automation and IT infrastructure management software company, best known for being co-founded by Marc Andreessen and later acquired by Hewlett-Packard.
  • 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_69a885f352a4819099b24ff15489dede completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a8872fae4c81908e7d6961e6c5fa96 completed March 4, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1cb578e4819082d254462e10e4f0 completed March 8, 2026, 6:52 a.m.
Created at: March 4, 2026, 7:24 p.m.