Triple
T14372601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Misfit Ray |
E356391
|
entity |
| Predicate | wearableCategory |
P21365
|
FINISHED |
| Object | health and fitness wearable |
—
|
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: health and fitness wearable | Statement: [Misfit Ray, wearableCategory, health and fitness wearable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearableCategory Context triple: [Misfit Ray, wearableCategory, health and fitness wearable]
-
A.
wearableBy
Indicates that one entity is designed or suitable to be worn on the body by another entity.
-
B.
wearerType
Indicates the type or category of entity that is intended to wear or use the associated item.
-
C.
wearerDevice
Indicates that a device is worn or carried by a particular entity (the wearer).
-
D.
wearClassification
chosen
Indicates a classification relationship specifying the type or category of wear associated with an entity or interaction.
-
E.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fb2082c8190b42cc5f2bab4f574 |
completed | April 14, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:15 a.m.