Triple
T3368774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Mosque of Kuwait |
E70901
|
entity |
| Predicate | prayerHallCapacity |
P47633
|
FINISHED |
| Object | about 10000 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: about 10000 worshippers | Statement: [Grand Mosque of Kuwait, prayerHallCapacity, about 10000 worshippers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prayerHallCapacity Context triple: [Grand Mosque of Kuwait, prayerHallCapacity, about 10000 worshippers]
-
A.
hasNumberOfMosques
Indicates the quantity of mosques associated with a given entity.
-
B.
isOneOfTheLargestMosquesIn
Indicates that the subject mosque ranks among the largest mosques located in the specified place or region.
-
C.
hasMosque
Indicates that one entity possesses, contains, or is the location of a mosque.
-
D.
numberOfBalconiesOnMinarets
Indicates the count of balconies present on the minarets associated with a given subject.
-
E.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69ada698eeb48190a1f5762fdd3b7b63 |
completed | March 8, 2026, 4:40 p.m. |
Created at: March 8, 2026, 3:13 p.m.