Triple
T29466817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Leader |
E747400
|
entity |
| Predicate | hasScriptInOriginal |
P102851
|
FINISHED |
| Object | Arabic script |
—
|
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: Arabic script | Statement: [The Leader, hasScriptInOriginal, Arabic script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScriptInOriginal Context triple: [The Leader, hasScriptInOriginal, Arabic script]
-
A.
hasOriginalScriptName
chosen
Indicates that an entity is associated with the name of its script or title as it appears in the original language or writing system.
-
B.
hasScriptBy
Indicates that one entity has its script authored, written, or created by another entity.
-
C.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
-
D.
hasScriptCode
Indicates that an entity is associated with a particular writing system identified by a specific script code.
-
E.
hasOriginalCompiler
Indicates that one entity is the original creator or compiler responsible for assembling or producing another entity.
- 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_69f0bd4125f88190b56104591351619c |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 28, 2026, 3:53 p.m.