Triple
T2401837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Rhys-Davies |
E47786
|
entity |
| Predicate | characterPortrayed |
P1507
|
FINISHED |
| Object | Sallah |
E224931
|
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: Sallah | Statement: [John Rhys-Davies, characterPortrayed, Sallah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sallah Context triple: [John Rhys-Davies, characterPortrayed, Sallah]
-
A.
Sallah
chosen
Sallah is a jovial, resourceful Egyptian excavator and close ally of Indiana Jones who helps him navigate dangerous archaeological adventures.
-
B.
Hassan
Hassan is a key antagonist in Lord Byron’s narrative poem "The Giaour," depicted as a powerful Ottoman leader whose actions drive the poem’s central conflict.
-
C.
Yahya
Yahya is the Islamic prophet identified with John the Baptist, revered for his piety, asceticism, and role in heralding the coming of Prophet Isa (Jesus).
-
D.
Mohamed
Mohamed is a common Arabic male given name, widely used across the Muslim world in honor of the Prophet Muhammad.
-
E.
Hamed
Hamed is a masculine given name commonly used in Arabic-speaking and Muslim-majority cultures.
- 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_69a88a1c450c81909f61abb8b6863885 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc8f623908190875fdbc95c944f33 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef09b92048190acfa3a85417f259c |
completed | March 9, 2026, 4:08 p.m. |
Created at: March 4, 2026, 7:57 p.m.