Triple
T28554237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magistrate Courts of Israel |
E722962
|
entity |
| Predicate | canUseLanguage |
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: [Magistrate Courts of Israel, canUseLanguage, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canUseLanguage Context triple: [Magistrate Courts of Israel, canUseLanguage, Arabic]
-
A.
usesLanguageFor
chosen
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
B.
usesLanguageAs
Indicates that one entity communicates or operates using another entity as its language or linguistic medium.
-
C.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
D.
hasStandardLanguageNearby
Indicates that a standard or commonly used language is present in close proximity to the referenced entity.
-
E.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6617ba4a88190bfc5c305acb4f93f |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 3:44 a.m.