Triple
T25944267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | المحكمة الدستورية العليا |
E653794
|
entity |
| Predicate | تختص |
P140458
|
FINISHED |
| Object | بمراقبة دستورية القرارات بقوانين |
—
|
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: بمراقبة دستورية القرارات بقوانين | Statement: [المحكمة الدستورية العليا, تختص, بمراقبة دستورية القرارات بقوانين]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تختص Context triple: [المحكمة الدستورية العليا, تختص, بمراقبة دستورية القرارات بقوانين]
-
A.
subjectSpecialization
chosen
Indicates that one subject focuses on, or has expertise in, a particular field, topic, or area of knowledge.
-
B.
laterSpecializedIn
Indicates that an entity initially engaged in a broader or different field and subsequently focused its work or expertise in a more specific or specialized area.
-
C.
specialRole
Indicates that an entity holds a distinctive or exceptional function, status, or responsibility in relation to another entity or context.
-
D.
primarilyEncompasses
Indicates that one entity mainly or predominantly includes, covers, or consists of another entity or set of entities.
-
E.
uniformSpecialty
Indicates that multiple entities share the same specific specialty, expertise, or area of focus.
- 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_69e7ab3fd2f881908837305e4ba98011 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60462fad88190be275c21dabc791c |
completed | May 2, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69f5afec3e94819080d9ba86cf8c866e |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 22, 2026, 8:41 a.m.