Triple
T1503445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cisco Meraki |
E33846
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Meraki MV |
E33847
|
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: Meraki MV | Statement: [Cisco Meraki, brand, Meraki MV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meraki MV Context triple: [Cisco Meraki, brand, Meraki MV]
-
A.
Meraki
chosen
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.
-
B.
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.
-
C.
Mvezo
Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
-
D.
Seabreeze
Seabreeze was a former neighboring city to Daytona Beach, Florida, that was eventually incorporated into the larger Daytona Beach municipality.
-
E.
Blisk
Blisk is a fictional setting or universe in which the character or concept known as Blink appears or is utilized.
- 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.