Triple
T34841466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kaba gaida |
E1004350
|
entity |
| Predicate | embellishment |
P23430
|
FINISHED |
| Object | often decorated with traditional motifs |
—
|
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: often decorated with traditional motifs | Statement: [kaba gaida, embellishment, often decorated with traditional motifs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: embellishment Context triple: [kaba gaida, embellishment, often decorated with traditional motifs]
-
A.
adornedWith
chosen
Indicates that one entity is decorated, embellished, or ornamented by another entity.
-
B.
enchantment
Indicates that one entity has placed a magical or supernatural influence on another, altering its state, behavior, or properties.
-
C.
exaggerates
Indicates that one entity portrays something about another entity or situation as greater, more extreme, or more significant than it actually is.
-
D.
enchantable
Indicates that an entity is capable of being affected by or imbued with magical enchantments.
-
E.
decorations
Indicates that one entity adds, provides, or serves as ornamental or decorative elements for another 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_69f76db97714819099b5bed36fd64e9d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.