Triple
T864916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sultan of the Ottoman Empire |
E18679
|
entity |
| Predicate | wore |
P271
|
FINISHED |
| Object | turban and imperial robes |
—
|
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: turban and imperial robes | Statement: [Sultan of the Ottoman Empire, wore, turban and imperial robes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wore Context triple: [Sultan of the Ottoman Empire, wore, turban and imperial robes]
-
A.
wears
chosen
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
B.
wornAs
Indicates that one entity is used or put on as clothing, an accessory, or a wearable item by another entity.
-
C.
wornFor
Indicates that an item is worn for a particular purpose, function, or occasion.
-
D.
wornAround
Indicates that one entity is physically worn encircling or surrounding another entity (e.g., around a body part or object).
-
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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac6acc148190bcc00a1e939ace77 |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa86065881909d477e26fdd84d45 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.