Triple
T31842697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | أحمد قريع |
E812848
|
entity |
| Predicate | سبب الشهرة |
P172659
|
FINISHED |
| Object | دوره في رئاسة الحكومة الفلسطينية |
—
|
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 رئاسة الحكومة الفلسطينية | Statement: [أحمد قريع, سبب الشهرة, دوره في رئاسة الحكومة الفلسطينية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: سبب الشهرة Context triple: [أحمد قريع, سبب الشهرة, دوره في رئاسة الحكومة الفلسطينية]
-
A.
مجال الشهرة
Indicates the domain or field in which an entity is renowned or widely recognized.
-
B.
سبب التسمية
Indicates the reason or cause behind assigning a particular name to something.
-
C.
السمعة
Indicates the reputation or public perception associated with an entity based on others’ opinions or past actions.
-
D.
سبب النزول
Indicates the relationship of being the specific cause, event, or circumstance that led to the revelation of a particular Quranic verse or passage.
-
E.
الحدث المشهور
Indicates that an event is widely known or well-recognized by many people.
- F. None of above. chosen
Provenance (4 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_69f348eb327881909b4584b925742f6e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b034bc74819091250f91ba5174c0 |
completed | May 3, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6af7d92008190aead47eaae8cc091 |
completed | May 3, 2026, 2:14 a.m. |
Created at: April 30, 2026, 11:49 p.m.