Triple
T4013379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Qarawiyyin Mosque |
E90697
|
entity |
| Predicate | mainPrayerHallType |
P53929
|
FINISHED |
| Object | hypostyle |
—
|
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: hypostyle | Statement: [al-Qarawiyyin Mosque, mainPrayerHallType, hypostyle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPrayerHallType Context triple: [al-Qarawiyyin Mosque, mainPrayerHallType, hypostyle]
-
A.
prayerHallCapacity
Indicates the maximum number of people that the prayer hall is designed or allowed to accommodate at one time.
-
B.
hasMosque
Indicates that one entity possesses, contains, or is the location of a mosque.
-
C.
templeType
Indicates the specific category or classification of a temple in terms of its form, function, or religious/architectural style.
-
D.
hasMihrab
Indicates that a structure or space contains or is equipped with a mihrab, the niche indicating the direction of prayer in a mosque or Islamic prayer area.
-
E.
containsPrayerType
Indicates that one entity includes or encompasses a specific type or category of prayer.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefaea76c48190add2e7cee180e8b1 |
completed | March 9, 2026, 4:52 p.m. |
Created at: March 9, 2026, 3:35 p.m.