Triple
T23736457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saudi judiciary |
E586552
|
entity |
| Predicate | usesLanguageInProceedings |
P108903
|
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: [Saudi judiciary, usesLanguageInProceedings, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLanguageInProceedings Context triple: [Saudi judiciary, usesLanguageInProceedings, Arabic]
-
A.
languageOfProceedingsOverseen
Indicates the language in which the proceedings that an entity oversees or presides over are conducted.
-
B.
usesLanguageFor
chosen
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
C.
hasAlternativeLanguageOfProceedings
Indicates that there exists another language in which the proceedings can officially be conducted or are available.
-
D.
usesLanguageAs
Indicates that one entity communicates or operates using another entity as its language or linguistic medium.
-
E.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
- 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_69e24907dc9c8190be074c9c96a0ec2d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bad28fa481909d7a6a6e98a7b0a5 |
completed | April 29, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:10 p.m.