Triple
T4687801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramy |
E103962
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Amr Waked |
E127934
|
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 Waked | Statement: [Ramy, starring, Amr Waked]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amr Waked Context triple: [Ramy, starring, Amr Waked]
-
A.
Amr Waked
chosen
Amr Waked is an Egyptian actor known internationally for his roles in films such as "Syriana," "Lucy," and "Salmon Fishing in the Yemen."
-
B.
Amr Khaled
Amr Khaled is a prominent Egyptian Muslim televangelist and Islamic preacher known for his popular satellite TV programs and modern, motivational style of religious outreach.
-
C.
Sinan al-Shabibi
Sinan al-Shabibi was an Iraqi economist best known for serving as governor of the Central Bank of Iraq, where he led major post-2003 monetary and financial reforms.
-
D.
Amr Diab
Amr Diab is a hugely popular Egyptian singer and composer, often called the "Father of Mediterranean Music" for blending Arabic and Western musical styles.
-
E.
Marwan Kenzari
Marwan Kenzari is a Dutch-Tunisian actor known for his roles in international films such as Disney’s live-action Aladdin and various Hollywood thrillers and dramas.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6397f6888190a9024a51d4d34f2b |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03b75e3481908aa27eeaeec490ca |
completed | March 21, 2026, 2:34 a.m. |
Created at: March 20, 2026, 1:16 p.m.