Triple
T16095591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dane |
E390474
|
entity |
| Predicate | modernUsageContext |
P121879
|
FINISHED |
| Object | nationality description |
—
|
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: nationality description | Statement: [Dane, modernUsageContext, nationality description]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernUsageContext Context triple: [Dane, modernUsageContext, nationality description]
-
A.
modernUse
Indicates how something is currently used or applied in modern times.
-
B.
contemporaryUse
Indicates that something is currently used or practiced in the present time or modern context.
-
C.
modernUsageRegion
Indicates the geographic region where something is currently or most commonly used in modern times.
-
D.
modernExample
Indicates that something serves as a contemporary or current-day instance or illustration of something else.
-
E.
originalUseContext
Indicates the original situation, setting, or context in which something was intended to be used or applied.
- F. None of above. chosen
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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e182804208819087f35307cd6e4103 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 4:59 a.m.