Triple
T3811670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Şehzade Mosque |
E93149
|
entity |
| Predicate | minaretFeatures |
P31119
|
FINISHED |
| Object | 2 balconies on each minaret |
—
|
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: 2 balconies on each minaret | Statement: [Şehzade Mosque, minaretFeatures, 2 balconies on each minaret]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minaretFeatures Context triple: [Şehzade Mosque, minaretFeatures, 2 balconies on each minaret]
-
A.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
B.
numberOfBalconiesOnMinarets
chosen
Indicates the count of balconies present on the minarets associated with a given subject.
-
C.
hasDomeAndMinarets
Indicates that something possesses both a dome and one or more minarets as architectural features.
-
D.
hasMinaretHeightApprox
Indicates that an entity has a minaret whose height is approximately a specified value, allowing for some margin of imprecision.
-
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.
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_69aed96a60088190ab1df8390fffc935 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7482d708190a3ec74745b102a4c |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:16 p.m.