Triple
T30111624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | محمد البرادعي |
E765291
|
entity |
| Predicate | سبب_الشهرة |
P100753
|
FINISHED |
| Object | دوره في الوكالة الدولية للطاقة الذرية |
—
|
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: دوره في الوكالة الدولية للطاقة الذرية | Statement: [محمد البرادعي, سبب_الشهرة, دوره في الوكالة الدولية للطاقة الذرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: سبب_الشهرة Context triple: [محمد البرادعي, سبب_الشهرة, دوره في الوكالة الدولية للطاقة الذرية]
-
A.
causeCélèbre
Indicates a relationship where an event, issue, or person becomes widely known and intensely debated or celebrated in public discourse.
-
B.
مجال الشهرة
Indicates the domain or field in which an entity is renowned or widely recognized.
-
C.
possibleCauseOfNotability
chosen
Indicates that one entity is a potential reason or contributing factor for why another entity is notable or recognized.
-
D.
basedOnFameFrom
Indicates that something is determined, influenced, or derived from the level or source of fame associated with an entity.
-
E.
genreOfNotoriety
Indicates that an entity is known or famous specifically for a particular genre or category.
- 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_69f22475ad7c8190be7f9541044a0bbb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67dbfc82081909ae5d04676627a6c |
completed | May 2, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:10 p.m.