Triple
T1946264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lezginka (Azerbaijani variant) |
E42060
|
entity |
| Predicate | hasCostumeElement |
P28106
|
FINISHED |
| Object | traditional Caucasian-style outfits |
—
|
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: traditional Caucasian-style outfits | Statement: [Lezginka (Azerbaijani variant), hasCostumeElement, traditional Caucasian-style outfits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCostumeElement Context triple: [Lezginka (Azerbaijani variant), hasCostumeElement, traditional Caucasian-style outfits]
-
A.
costumeElement
chosen
Indicates that one item functions as a component or part of another item's costume.
-
B.
haveDistinctCostume
Indicates that the entities each possess a costume that is different from the others’ costumes.
-
C.
usesElement
Indicates that one entity makes use of, incorporates, or depends on a specified element in its structure, function, or behavior.
-
D.
hasCosmetics
Indicates that one entity possesses, uses, or is associated with cosmetic products or beauty-related items in relation to another entity or context.
-
E.
isCostumed
Indicates that an entity is wearing or otherwise adorned with a costume.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb32ebae881908f7541301f0198ae |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff25a588190bb4cbc8df9fc6d64 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.