Triple
T1988271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mataf area |
E43189
|
entity |
| Predicate | hasFloorLevel |
P24577
|
FINISHED |
| Object | ground level around Kaaba |
—
|
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: ground level around Kaaba | Statement: [Mataf area, hasFloorLevel, ground level around Kaaba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloorLevel Context triple: [Mataf area, hasFloorLevel, ground level around Kaaba]
-
A.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
-
B.
hasUpperFloor
Indicates that one entity possesses or includes an upper floor relative to another level or reference point.
-
C.
hasGroundFloor
chosen
Indicates that a building or structure includes a ground-level floor as part of its layout or design.
-
D.
hasFloorMaterial
Indicates that an entity’s floor is made of, covered with, or constructed from a specified material.
-
E.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.