Triple
T12093836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Cambridge |
E288015
|
entity |
| Predicate | titleBecameCourtesy |
P81246
|
FINISHED |
| Object | when holder created Prince 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: when holder created Prince of Wales | Statement: [Duke of Cambridge, titleBecameCourtesy, when holder created Prince of Wales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleBecameCourtesy Context triple: [Duke of Cambridge, titleBecameCourtesy, when holder created Prince of Wales]
-
A.
usedAsCourtesyTitleFor
chosen
Indicates that one entity serves as a courtesy title or honorific form of address applied to another entity.
-
B.
titleBecomes
Indicates that one title changes into or is replaced by another title over time.
-
C.
usedAsTitleUntil
Indicates that a particular title was held or used by an entity up to (and including or until) a specified end time.
-
D.
titleThrough
Indicates a relationship where one entity holds or is identified by a specific title by means of, or via the mediation of, another entity or context.
-
E.
titleVariant
Indicates that one title is an alternative or variant form of another title referring to the same work or entity.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.