Triple
T21965588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Muizz li-Din Allah Street |
E542446
|
entity |
| Predicate | hasBuildingTypeConcentration |
P50464
|
FINISHED |
| Object | 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: mosques | Statement: [Al-Muizz li-Din Allah Street, hasBuildingTypeConcentration, mosques]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingTypeConcentration Context triple: [Al-Muizz li-Din Allah Street, hasBuildingTypeConcentration, mosques]
-
A.
containsBuildingType
chosen
Indicates that a location or area includes at least one building of the specified type.
-
B.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
C.
hasMunicipalBuildings
Indicates that a place or jurisdiction possesses one or more buildings used for municipal or local government functions.
-
D.
hasResidentialBuildingsType
Indicates that an entity is associated with a specific type or category of residential buildings.
-
E.
hasBuildingClass
Indicates that a building is categorized as belonging to a specific building class or type.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1245aabf88190a44564e6eaaa94ce |
completed | April 28, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 8:01 p.m.