Triple
T1378886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abdullah ibn Muhammad |
E29290
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Abdullah |
E112184
|
NE 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: Abdullah | Statement: [Abdullah ibn Muhammad, givenName, Abdullah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abdullah Context triple: [Abdullah ibn Muhammad, givenName, Abdullah]
-
A.
Abdullah
chosen
Abdullah is a common Arabic male given name, notably borne by King Abdullah II of Jordan.
-
B.
Abdullah ibn Muhammad
Abdullah ibn Muhammad was one of the sons of the Islamic prophet Muhammad who died in early childhood.
-
C.
Fahd
Fahd is a male given name of Arabic origin, notably borne by King Fahd of Saudi Arabia.
-
D.
Hussein
Hussein is a common Arabic surname and given name, notably borne by former Iraqi president Saddam Hussein.
-
E.
Abdus
Abdus is a given name most notably borne by Abdus Salam, the Pakistani theoretical physicist and Nobel laureate.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3187f248190a5813274b0ef944d |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad293ab8508190ac321c898cd3df39 |
completed | March 8, 2026, 7:46 a.m. |
Created at: March 1, 2026, 7:59 p.m.