Triple
T6318553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faten Hamama |
E141676
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Yom Saeed |
E141676
|
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: Yom Saeed | Statement: [Faten Hamama, notableWork, Yom Saeed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yom Saeed Context triple: [Faten Hamama, notableWork, Yom Saeed]
-
A.
Yom Saeed
chosen
Yom Saeed is an early Egyptian film notable for featuring the debut screen appearance of legendary actress Faten Hamama.
-
B.
Salah Abu Seif
Salah Abu Seif was a pioneering Egyptian film director widely regarded as the father of realism in Egyptian cinema.
-
C.
Zaki Salam
Zaki Salam is a notable individual recognized as a distinguished bearer of the surname Salam.
-
D.
Saad Haddad
Saad Haddad was a Lebanese militia leader and army officer who founded and commanded the Israeli-backed South Lebanon Army during the Lebanese Civil War.
-
E.
Anas al-Abdah
Anas al-Abdah is a Syrian opposition politician who has held senior leadership roles in exile-based bodies opposing Bashar al-Assad’s government during the Syrian Civil War.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c38fe48190a71a4e5e1af19b10 |
completed | March 22, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65fb7e7c88190bef0a15c12250b13 |
completed | March 27, 2026, 10:45 a.m. |
Created at: March 22, 2026, 4:29 p.m.