Triple
T10213108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rockstar |
E242377
|
entity |
| Predicate | leadActress |
P6108
|
FINISHED |
| Object | Nargis Fakhri |
E849902
|
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: Nargis Fakhri | Statement: [Rockstar, leadActress, Nargis Fakhri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nargis Fakhri Context triple: [Rockstar, leadActress, Nargis Fakhri]
-
A.
Nargis Fakhri
chosen
Nargis Fakhri is an American-born actress and model of Pakistani-Czech descent who gained prominence in Indian cinema with her debut in the film "Rockstar."
-
B.
Faten Hamama
Faten Hamama was a renowned Egyptian film actress often hailed as the "Lady of the Arabic Screen" and a central figure in the golden age of Egyptian cinema.
-
C.
Fatimah el-Sharif
Fatimah el-Sharif was the Queen consort of Libya as the wife of King Idris I and a member of the prominent Senussi family.
-
D.
Hamida Mohammad Ali
Hamida Mohammad Ali was the wife of Pakistani statesman and former Prime Minister Mohammad Ali Bogra.
-
E.
Hani Nassar
Hani Nassar is an individual notable enough to be specifically cited as a bearer of the surname Nassar.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa24efc081909714d98943543283 |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a7f6730081908b941eaeb6c00993 |
completed | April 8, 2026, 7:09 p.m. |
Created at: April 6, 2026, 11:03 a.m.