Triple
T26500299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الملك فهد بن عبد العزيز آل سعود |
E669400
|
entity |
| Predicate | المنصب السابق |
P72167
|
FINISHED |
| Object | وزير الداخلية السعودي |
—
|
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: وزير الداخلية السعودي | Statement: [الملك فهد بن عبد العزيز آل سعود, المنصب السابق, وزير الداخلية السعودي]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: المنصب السابق Context triple: [الملك فهد بن عبد العزيز آل سعود, المنصب السابق, وزير الداخلية السعودي]
-
A.
بداية المنصب
Indicates the starting point in time when an entity officially assumes a position or office.
-
B.
previousOffice
chosen
Indicates that one office or position was held immediately before another in a sequence of offices.
-
C.
officePreviouslyHeldBy
Indicates that a particular office or position was formerly occupied by a specified person or entity.
-
D.
夫の地位
Indicates the social or professional status or position held by a husband in relation to others.
-
E.
النشاط الرئيس
Indicates that one entity is the primary or main activity associated with another entity.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b3a8ae0819090189fbd8eb19f2f |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 1:12 a.m.