Triple
T5021181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sultan Qaboos Grand Mosque |
E112850
|
entity |
| Predicate | hasCourtyardCapacity |
P16753
|
FINISHED |
| Object | over 8000 worshippers |
—
|
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: over 8000 worshippers | Statement: [Sultan Qaboos Grand Mosque, hasCourtyardCapacity, over 8000 worshippers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourtyardCapacity Context triple: [Sultan Qaboos Grand Mosque, hasCourtyardCapacity, over 8000 worshippers]
-
A.
courtyardCapacity
chosen
Indicates the maximum number of entities that can be accommodated in a courtyard at the same time.
-
B.
hasCourtyardArea
Indicates that an entity includes or is associated with a courtyard and specifies the size or extent of that courtyard space.
-
C.
hasCourtyard
Indicates that one entity includes, features, or is characterized by the presence of a courtyard.
-
D.
courtyardType
Indicates the specific kind or classification of a courtyard associated with an entity.
-
E.
hasOrchestraPitCapacity
Indicates the number of people that can be accommodated in the orchestra pit associated with a venue or performance space.
- 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.