Triple
T22658083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | يوسف والي |
E559283
|
entity |
| Predicate | كان شخصية مثيرة للجدل في |
P81772
|
FINISHED |
| Object | السياسة المصرية |
—
|
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: السياسة المصرية | Statement: [يوسف والي, كان شخصية مثيرة للجدل في, السياسة المصرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: كان شخصية مثيرة للجدل في Context triple: [يوسف والي, كان شخصية مثيرة للجدل في, السياسة المصرية]
-
A.
roleInControversy
Indicates the specific part, involvement, or function an entity has within a particular controversy or disputed situation.
-
B.
hasControversialAspect
chosen
Indicates that something includes an element, feature, or aspect that is disputed, debated, or likely to cause disagreement or public criticism.
-
C.
controversialBecause
Indicates that one entity is considered controversial specifically due to, or as a result of, its relationship with or association to another entity.
-
D.
questionedCharacter
Indicates that one entity directed questions or an interrogation toward another entity.
-
E.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765d10588190b4574f3e64617cd4 |
completed | April 29, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:07 p.m.