Triple
T11939136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Lumia 950 |
E284127
|
entity |
| Predicate | hasSensors |
P17204
|
FINISHED |
| Object | accelerometer |
—
|
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: accelerometer | Statement: [Microsoft Lumia 950, hasSensors, accelerometer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSensors Context triple: [Microsoft Lumia 950, hasSensors, accelerometer]
-
A.
hasSensor
chosen
Indicates that one entity is equipped with, contains, or uses a particular sensor.
-
B.
hasSensation
Indicates that an entity experiences or is subject to a particular sensory or perceptual feeling.
-
C.
hasSensoryOrgans
Indicates that an entity possesses organs specialized for sensing or perceiving stimuli from its environment.
-
D.
sensingAction
Indicates an action in which an entity perceives, detects, or measures some property, signal, or condition of another entity or its environment.
-
E.
hasElectronicsFeature
Indicates that an entity possesses or is characterized by a specific electronic-related feature or 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903415d2481909d84e6727454b9fe |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.