Triple
T37658873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia Asha 200 |
E937667
|
entity |
| Predicate | USBConnectorType |
P100239
|
FINISHED |
| Object | microUSB |
—
|
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: microUSB | Statement: [Nokia Asha 200, USBConnectorType, microUSB]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: USBConnectorType Context triple: [Nokia Asha 200, USBConnectorType, microUSB]
-
A.
hasUSBConnectorType
chosen
Indicates the specific type or standard of USB connector associated with a device or component.
-
B.
connectorType
Indicates the specific kind or category of connection interface that links two entities.
-
C.
hasUSBPort
Indicates that one entity is equipped with or includes a USB port available for connection or data/power transfer.
-
D.
connectorTypeDesignation
Indicates the specific type or classification assigned to a connector within a connection or interface relationship.
-
E.
supportsPCConnectivity
Indicates that one entity enables or is compatible with connection or communication to a personal computer.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa1321b48190af92a3e7ec24ec5b |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.