Triple
T3909133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruqʿah |
E87278
|
entity |
| Predicate | strokeOrder |
P20863
|
FINISHED |
| Object | optimized for speed |
—
|
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: optimized for speed | Statement: [Ruqʿah, strokeOrder, optimized for speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: strokeOrder Context triple: [Ruqʿah, strokeOrder, optimized for speed]
-
A.
hasStrokeOrder
chosen
Indicates that there is a specific, ordered sequence of strokes used to write or draw the related symbol or character.
-
B.
kuficOrder
Indicates that one entity commissions, arranges, or prescribes the creation or use of Kufic script in relation to another entity.
-
C.
inscriptionLayout
Indicates how an inscription is spatially arranged or formatted in relation to the surface or object it appears on.
-
D.
hasStrokeCountApprox
Indicates an approximate number of strokes associated with writing or drawing the related entity.
-
E.
isCursive
Indicates that the referenced writing or text is in cursive (joined, flowing handwriting) form.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.