Triple
T3368775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Mosque of Kuwait |
E70901
|
entity |
| Predicate | overallCapacity |
P13466
|
FINISHED |
| Object | more than 50000 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: more than 50000 worshippers | Statement: [Grand Mosque of Kuwait, overallCapacity, more than 50000 worshippers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: overallCapacity Context triple: [Grand Mosque of Kuwait, overallCapacity, more than 50000 worshippers]
-
A.
totalCapacity
chosen
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
B.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
C.
installedCapacity
Indicates the maximum output or production capability that has been set up or built for a system, facility, or equipment, typically measured under specified conditions.
-
D.
capacityCategory
Indicates the classification of something based on the amount or volume it can hold, handle, or accommodate.
-
E.
annualCapacity
Indicates the maximum amount of output or throughput an entity can produce or handle within a one-year period.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28a813c81909d1c71fe577e6681 |
completed | March 8, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69ada4317e288190ab7d0f66e9dba65f |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.