Triple
T20570047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mosque with Three Balconies |
E505069
|
entity |
| Predicate | hasMinaretCountWithBalconies |
P31119
|
FINISHED |
| Object | one minaret with three balconies |
—
|
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: one minaret with three balconies | Statement: [Mosque with Three Balconies, hasMinaretCountWithBalconies, one minaret with three balconies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinaretCountWithBalconies Context triple: [Mosque with Three Balconies, hasMinaretCountWithBalconies, one minaret with three balconies]
-
A.
numberOfBalconiesOnMinarets
chosen
Indicates the count of balconies present on the minarets associated with a given subject.
-
B.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
C.
hasDomeAndMinarets
Indicates that something possesses both a dome and one or more minarets as architectural features.
-
D.
floorCountOfMinaret
Indicates the number of floors or levels that a minaret has.
-
E.
hasMihrabCount
Indicates the number of mihrabs associated with or present in a given entity or structure.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a7a5b0688190b45d0fa993c4765c |
completed | April 20, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.