Triple
T22059863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badr bin Abdullah bin Mohammed bin Farhan Al Saud |
E545122
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Abdullah |
—
|
NE NERFINISHED |
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: Abdullah | Statement: [Badr bin Abdullah bin Mohammed bin Farhan Al Saud, givenName, Abdullah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abdullah Context triple: [Badr bin Abdullah bin Mohammed bin Farhan Al Saud, givenName, Abdullah]
-
A.
Abdullah
chosen
Abdullah is a common Arabic male given name, notably borne by King Abdullah II of Jordan.
-
B.
Abdulla
Abdulla is a character in Ngũgĩ wa Thiong'o's novel "Petals of Blood," representing the struggles and transformations of ordinary Kenyans in the postcolonial era.
-
C.
Abdulrahman
Abdulrahman is a masculine given name of Arabic origin meaning "servant of the Most Merciful," commonly used across the Muslim world.
-
D.
Ahmad
Ahmad is the narrator of the film "Soul Food," providing the story’s perspective and emotional throughline.
-
E.
Ahmad
Ahmad is the deposed king and heroic protagonist in the 1940 fantasy film "The Thief of Bagdad."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3377c48190890c17407b9527d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285ba1c88190b4bc0c73f3cf04e1 |
completed | April 28, 2026, 9:36 p.m. |
Created at: April 16, 2026, 8:27 p.m.