Triple
T20654536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold Macmillan in The Crown |
E507586
|
entity |
| Predicate | depictsAspectOf |
P53700
|
FINISHED |
| Object | British constitutional monarchy |
—
|
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: British constitutional monarchy | Statement: [Harold Macmillan in The Crown, depictsAspectOf, British constitutional monarchy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsAspectOf Context triple: [Harold Macmillan in The Crown, depictsAspectOf, British constitutional monarchy]
-
A.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
-
B.
isDepictedVia
Indicates that one entity is represented, illustrated, or shown by means of another entity, such as a specific medium, style, or method of depiction.
-
C.
typicallyDepicts
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
-
D.
depictsView
Indicates that one entity visually represents or portrays the view, scene, or perspective of another entity.
-
E.
depictsAttribute
chosen
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2ec90e881909250884483429acf |
completed | April 20, 2026, 11:12 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.