Triple
T1158098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Azhar Mosque |
E24429
|
entity |
| Predicate | numberOfMinarets |
P11839
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Al-Azhar Mosque, numberOfMinarets, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMinarets Context triple: [Al-Azhar Mosque, numberOfMinarets, multiple]
-
A.
hasMinarets
chosen
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
B.
hasMinaretHeightApprox
Indicates that an entity has a minaret whose height is approximately a specified value, allowing for some margin of imprecision.
-
C.
numberOfTowers
Indicates the quantity of towers associated with or contained by a given entity.
-
D.
towerName
Indicates the specific name assigned to a tower in the relationship.
-
E.
associatedCaliph
Indicates a relationship where an entity is linked or connected to a specific caliph, typically through rule, patronage, affiliation, or historical association.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcab3cd08190ad06ea007042a8fc |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb525b648190adcb7a29256d3c41 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:45 p.m.