Triple
T25814352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الروضة الشريفة |
E650207
|
entity |
| Predicate | hasFloorMarking |
P51959
|
FINISHED |
| Object | سجاد أخضر مميز |
—
|
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: سجاد أخضر مميز | Statement: [الروضة الشريفة, hasFloorMarking, سجاد أخضر مميز]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloorMarking Context triple: [الروضة الشريفة, hasFloorMarking, سجاد أخضر مميز]
-
A.
hasFloorMarkings
chosen
Indicates that an entity features visible markings or lines on its floor surface, typically used for guidance, organization, or safety.
-
B.
hasFloorColor
Indicates that an entity possesses a floor whose surface is characterized by a specific color.
-
C.
hasPavementPattern
Indicates that an entity possesses or is characterized by a specific pattern or design in its pavement surface.
-
D.
hasRunwayMarkings
Indicates that a runway possesses specific painted markings or symbols on its surface.
-
E.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f603bb02288190b40cedbed5b9651d |
completed | May 2, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 22, 2026, 7:12 a.m.