Triple
T9480496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ʿAmr |
E228623
|
entity |
| Predicate | hasTransliteration |
P2508
|
FINISHED |
| Object | Amr |
E30384
|
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: Amr | Statement: [ʿAmr, hasTransliteration, Amr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amr Context triple: [ʿAmr, hasTransliteration, Amr]
-
A.
Amr
chosen
Amr is a common Arabic male given name, often associated with historical and contemporary figures across the Arab world.
-
B.
Mahmoud
Mahmoud is a common Arabic male given name widely used across the Middle East and Muslim-majority countries.
-
C.
Ahmed
Ahmed is a common Arabic male given name meaning "most commendable" or "most praiseworthy."
-
D.
Sallah
Sallah is a jovial, resourceful Egyptian excavator and close ally of Indiana Jones who helps him navigate dangerous archaeological adventures.
-
E.
Mohamed
Mohamed is a common Arabic male given name, widely used across the Muslim world in honor of the Prophet Muhammad.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd8018645c8190823d82a93635b345 |
completed | April 1, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d139f261248190b8e3238f7618191d |
completed | April 4, 2026, 4:18 p.m. |
Created at: March 30, 2026, 7:54 p.m.