Triple
T10480166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | مستقبل وطن |
E247148
|
entity |
| Predicate | الصفة_القانونية |
P76736
|
FINISHED |
| Object | حزب مسجل وفق القانون المصري للأحزاب السياسية |
—
|
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: حزب مسجل وفق القانون المصري للأحزاب السياسية | Statement: [مستقبل وطن, الصفة_القانونية, حزب مسجل وفق القانون المصري للأحزاب السياسية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الصفة_القانونية Context triple: [مستقبل وطن, الصفة_القانونية, حزب مسجل وفق القانون المصري للأحزاب السياسية]
-
A.
juridicalCategory
chosen
Indicates the legal classification or status under which an entity or relationship is formally recognized in a juridical system.
-
B.
lawCharacteristicInText
Indicates that a specific legal characteristic or feature is expressed, described, or referenced within a given text.
-
C.
legalConcept
Indicates a relationship where something is classified or treated as a concept defined and governed by law or legal theory.
-
D.
featuresLaw
Indicates that something includes, presents, or is characterized by a particular law or legal provision.
-
E.
legalCodeName
Indicates that one entity is the official legal code designation or name assigned to another entity within a legal or regulatory system.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5095b2ec881909e1220d83e750a75 |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:22 p.m.