Triple
T4013383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Qarawiyyin Mosque |
E90697
|
entity |
| Predicate | minaretShape |
P53930
|
FINISHED |
| Object | square |
—
|
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: square | Statement: [al-Qarawiyyin Mosque, minaretShape, square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minaretShape Context triple: [al-Qarawiyyin Mosque, minaretShape, square]
-
A.
hasDomeAndMinarets
Indicates that something possesses both a dome and one or more minarets as architectural features.
-
B.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
C.
hasMinaretHeightApprox
Indicates that an entity has a minaret whose height is approximately a specified value, allowing for some margin of imprecision.
-
D.
numberOfBalconiesOnMinarets
Indicates the count of balconies present on the minarets associated with a given subject.
-
E.
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.
- 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.