Triple
T27327147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchess of Cambridge |
E689683
|
entity |
| Predicate | currentUsageContext |
P121879
|
FINISHED |
| Object | commonly used in media for Catherine, Princess of Wales |
—
|
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: commonly used in media for Catherine, Princess of Wales | Statement: [Duchess of Cambridge, currentUsageContext, commonly used in media for Catherine, Princess of Wales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentUsageContext Context triple: [Duchess of Cambridge, currentUsageContext, commonly used in media for Catherine, Princess of Wales]
-
A.
modernUsageContext
chosen
Indicates the contemporary or current context in which something is used, applied, or functions.
-
B.
contextType
Indicates the type or category of contextual information associated with an entity or event.
-
C.
currentSiteUse
Indicates how a site is presently being used or the function it currently serves.
-
D.
acquisitionContext
Indicates the circumstances, conditions, or setting under which an acquisition or purchase takes place.
-
E.
originalUseContext
Indicates the original situation, setting, or context in which something was intended to be used or applied.
- 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_69ef355d4cb08190ab032c0a2e7d3753 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f7b2f3a104819098ddd8909eaf596c |
completed | May 3, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
Created at: April 27, 2026, 11:36 a.m.