Triple
T1503414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cisco Meraki |
E33846
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Meraki |
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 | Statement: [Cisco Meraki, formerName, Meraki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meraki Context triple: [Cisco Meraki, formerName, Meraki]
-
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.
Telos
Telos is an icy, subterranean planet in the Doctor Who universe best known as a major stronghold and tomb world of the Cybermen.
-
C.
Nicado
Nicado is a Spanish-language surname most notably borne by Cuban mathematician and academic leader Miriam Nicado García.
-
D.
Nesta
Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
-
E.
Hespere
Hespere is one of the Hesperides, the nymphs of Greek mythology who tended the blissful garden in the far west that contained the golden apples.
- 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.