Triple
T311859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naskh script |
E7624
|
entity |
| Predicate | typicalUseComparedToThuluth |
P11832
|
FINISHED |
| Object | used for body text rather than large headings |
—
|
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: used for body text rather than large headings | Statement: [Naskh script, typicalUseComparedToThuluth, used for body text rather than large headings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseComparedToThuluth Context triple: [Naskh script, typicalUseComparedToThuluth, used for body text rather than large headings]
-
A.
dominantStyleForArabicTexts
Indicates the prevailing or primary stylistic form used when presenting or formatting Arabic texts.
-
B.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
-
C.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
D.
hasCursiveJoining
Indicates that one written character is connected to another through cursive-style joining.
-
E.
hasContextualLetterForms
Indicates that the written form of a letter changes shape depending on its surrounding characters or position within a word.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea49636c8190a69cbd951fc0a4db |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e940b9e8819092b821ff17ed026b |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea08878c8190a5e8a90f620a3888 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:07 p.m.