Triple
T4430913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jahra |
E95324
|
entity |
| Predicate | scriptForName |
P29837
|
FINISHED |
| Object | Arabic |
—
|
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 | Statement: [Jahra, scriptForName, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptForName Context triple: [Jahra, scriptForName, Arabic]
-
A.
scriptName
chosen
Indicates the name or title of a script associated with an entity, typically identifying which script is used, referenced, or executed in a given context.
-
B.
scriptOfSymbol
Indicates that one symbol is written or represented using the writing system or script associated with another symbol.
-
C.
scriptBlockName
Indicates that a specific block of script or code is identified or labeled by a given name.
-
D.
scriptWriter
Indicates that one entity is the person who wrote or authored the script associated with another entity.
-
E.
script
Indicates that an entity is associated with a written text or code (such as a screenplay, program, or written instructions) that defines its content or behavior.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3556b71448190a3fab938853f8b87 |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f6078cc8190831b89f404198cc5 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:31 p.m.