Triple
T12684824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia E55 |
E303039
|
entity |
| Predicate | hasDigitalCompass |
P35891
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Nokia E55, hasDigitalCompass, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDigitalCompass Context triple: [Nokia E55, hasDigitalCompass, true]
-
A.
hasMagneticHeading
Indicates the directional orientation of an entity relative to magnetic north, typically expressed as a magnetic compass bearing.
-
B.
hasMagneticHeadingRangeInDegrees
Indicates the range of possible magnetic heading values, measured in degrees, associated with an entity’s orientation or navigation.
-
C.
hasNavigationTechnology
chosen
Indicates that an entity is equipped with or utilizes a system or technology for determining or guiding its position, route, or movement.
-
D.
hasProximitySensor
Indicates that an entity is equipped with a sensor capable of detecting nearby objects or measuring its distance to them.
-
E.
hasDigitalFocus
Indicates that an entity is primarily oriented toward or centered on digital technologies, channels, or activities.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961d7cd4c81909521839ef5859799 |
completed | April 10, 2026, 8:47 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:21 p.m.