Triple
T35999201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zefta |
E1041080
|
entity |
| Predicate | usesWritingSystemOfCountry |
P26603
|
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: [Zefta, usesWritingSystemOfCountry, Arabic script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWritingSystemOfCountry Context triple: [Zefta, usesWritingSystemOfCountry, Arabic script]
-
A.
hasOfficialWritingSystem
Indicates that an entity (typically a language) is associated with a formally recognized and standardized writing system used for official or standard purposes.
-
B.
writingSystemUsedIn
chosen
Indicates that a particular writing system is employed for written communication within a given language, region, or context.
-
C.
hasWritingSystemForMajorLanguage
Indicates that there exists a writing system used to represent a major language associated with the given entity.
-
D.
writingSystemDevelopedFor
Indicates that a particular writing system was created or adapted specifically to be used for a given language, community, or purpose.
-
E.
usesWritingLanguage
Indicates that an entity communicates or produces written content using a particular language.
- 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_69f76e29084c819083987b828d414de7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.