Triple
T13024955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia 3000 classic |
E326277
|
entity |
| Predicate | hasOperatingMode |
P12713
|
FINISHED |
| Object | standalone mobile device |
—
|
LITERAL 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: standalone mobile device | Statement: [Nokia 3000 classic, hasOperatingMode, standalone mobile device]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOperatingMode Context triple: [Nokia 3000 classic, hasOperatingMode, standalone mobile device]
-
A.
hasWorkingMode
chosen
Indicates that an entity operates under or supports a particular mode or configuration of functioning.
-
B.
hasOperatingMIC
Indicates that an entity operates or manages a specific MIC (Market Identifier Code) in a financial or trading context.
-
C.
hasModeConnection
Indicates a relationship where one entity is linked to another through a specific mode, method, or type of connection.
-
D.
operatingStatus
Indicates whether an entity is currently functioning, active, or in service versus inactive, closed, or out of service.
-
E.
hasOperationalComponent
Indicates that an entity includes, uses, or depends on another entity as a functional or operational part of its overall system or process.
- F. None of above.
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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efac71881908a21d70c3c6ce099 |
completed | April 10, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69d97dc39a0881908119c62e31bf6182 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:53 p.m.