Triple
T5021152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sultan Qaboos Grand Mosque |
E112850
|
entity |
| Predicate | mainMinaretHeight |
P16755
|
FINISHED |
| Object | about 90 meters |
—
|
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: about 90 meters | Statement: [Sultan Qaboos Grand Mosque, mainMinaretHeight, about 90 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainMinaretHeight Context triple: [Sultan Qaboos Grand Mosque, mainMinaretHeight, about 90 meters]
-
A.
hasMinaretHeightApprox
chosen
Indicates that an entity has a minaret whose height is approximately a specified value, allowing for some margin of imprecision.
-
B.
floorCountOfMinaret
Indicates the number of floors or levels that a minaret has.
-
C.
numberOfBalconiesOnMinarets
Indicates the count of balconies present on the minarets associated with a given subject.
-
D.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
E.
minaretShape
Indicates that one entity has the specified architectural shape or form of a minaret in relation to 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736399ac8190aa38efc4b4edc6a2 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.