Triple
T38644247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mechagnomes |
E938674
|
entity |
| Predicate | cosmeticFeature |
P31173
|
FINISHED |
| Object | visible mechanical arms |
—
|
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: visible mechanical arms | Statement: [Mechagnomes, cosmeticFeature, visible mechanical arms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cosmeticFeature Context triple: [Mechagnomes, cosmeticFeature, visible mechanical arms]
-
A.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
B.
cosmeticCategory
Indicates that one entity is classified as belonging to a particular cosmetic or beauty product category defined by the other entity.
-
C.
facialMarkings
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
-
D.
hasPhysicalFeature
chosen
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
-
E.
faceliftFeature
Indicates that one entity is a specific feature, component, or aspect involved in a facelift procedure or facelift-related modification of the other entity.
- 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_69f76ed948ec81908ce7811608a8f359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.