Triple
T29440044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aguls |
E746685
|
entity |
| Predicate | traditionalClothingRegion |
P181207
|
FINISHED |
| Object | Caucasian highlands |
E1531714
|
NE 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: Caucasian highlands | Statement: [Aguls, traditionalClothingRegion, Caucasian highlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalClothingRegion Context triple: [Aguls, traditionalClothingRegion, Caucasian highlands]
-
A.
traditionalDressRegion
chosen
Indicates the geographic region or area with which a particular traditional dress is associated or from which it originates.
-
B.
nationalDress
Indicates that an item of clothing is recognized as the traditional or customary dress associated with a particular nation or culture.
-
C.
traditionalLifestyleRegion
Indicates that a region is characterized by or associated with a traditional lifestyle or way of living.
-
D.
culturalRegion
Indicates that an entity is located in, associated with, or belongs to a specific cultural region or cultural area.
-
E.
traditionalDressVariant
Indicates that one traditional dress is a variant or localized form of another traditional dress within the same broader cultural or stylistic tradition.
- F. None of above.
Provenance (4 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd6a1c1c4881908090053bc359b181 |
completed | May 8, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25f1075eb881908530641f191f77d9 |
completed | June 7, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69fd696f24d8819091033afacbdaadc5 |
completed | May 8, 2026, 4:41 a.m. |
Created at: April 28, 2026, 3:21 p.m.