Triple
T9384285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Az-Zukhruf |
E225865
|
entity |
| Predicate | mentionsTheme |
P831
|
FINISHED |
| Object | folly of worldly adornments |
—
|
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: folly of worldly adornments | Statement: [Az-Zukhruf, mentionsTheme, folly of worldly adornments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentionsTheme Context triple: [Az-Zukhruf, mentionsTheme, folly of worldly adornments]
-
A.
notableTheme
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
-
B.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
C.
followsInTheme
Indicates that one element continues or succeeds another while maintaining the same theme or thematic context.
-
D.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
E.
mentions
chosen
Indicates that one entity refers to, cites, or brings up another entity in some form of communication or content.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50c23e7881908112597a1771afa5 |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:44 p.m.