Triple
T2349656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zagazig |
E47415
|
entity |
| Predicate | hasMosque |
P38665
|
FINISHED |
| Object | multiple large mosques |
—
|
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 large mosques | Statement: [Zagazig, hasMosque, multiple large mosques]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMosque Context triple: [Zagazig, hasMosque, multiple large mosques]
-
A.
hasNumberOfMosques
Indicates the quantity of mosques associated with a given entity.
-
B.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
C.
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.
-
D.
functionStartAsMosque
Indicates that a building or structure originally began its use or function as a mosque.
-
E.
hasImam
Indicates that an entity is associated with, led by, or served by a particular imam in a religious or community context.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcb7ebb708190ba7edffee3c45d8b |
completed | March 7, 2026, 6:53 a.m. |
Created at: March 4, 2026, 7:54 p.m.