Triple
T11976896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Lumia 532 |
E285062
|
entity |
| Predicate | supportsCellularNetwork |
P46630
|
FINISHED |
| Object | GSM |
—
|
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: GSM | Statement: [Microsoft Lumia 532, supportsCellularNetwork, GSM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCellularNetwork Context triple: [Microsoft Lumia 532, supportsCellularNetwork, GSM]
-
A.
hasCellularComponent
Indicates that an entity possesses, includes, or is associated with a specific cellular component as part of its structure or organization.
-
B.
cellularOptions
Indicates that one entity specifies or provides available cellular network or mobile connectivity options for another entity.
-
C.
supportsEsim
Indicates that one entity provides compatibility with, or the ability to use, an embedded SIM (eSIM) for another entity.
-
D.
hasCellService
chosen
Indicates that a location, device, or area is within range of a cellular network and can access mobile phone or data services.
-
E.
supportsTethering
Indicates that one entity enables or allows another entity to share its network connection with additional devices (i.e., provides tethering capability).
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903acbb9081908fe7f8360057785c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.