Triple
T4524686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shabana Rehman |
E103348
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Shabana |
E175229
|
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: Shabana | Statement: [Shabana Rehman, givenName, Shabana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shabana Context triple: [Shabana Rehman, givenName, Shabana]
-
A.
Shabana
chosen
Shabana is a prominent Bangladeshi film actress renowned for her extensive and influential career in Bengali cinema.
-
B.
Salma
Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
-
C.
Zohra
Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
-
D.
Sufiya Zinobia
Sufiya Zinobia is a central character in Salman Rushdie’s novel "Shame," symbolizing purity, repression, and the violent consequences of societal and familial pressures in a fictionalized Pakistan.
-
E.
Wafa Begum
Wafa Begum was a queen consort of the Durrani Empire as the wife of Afghan ruler Shuja Shah Durrani.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5773341c8190bf27745feb863575 |
completed | March 20, 2026, 2:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bda4483aa481909a100bf20085d667 |
completed | March 20, 2026, 7:47 p.m. |
Created at: March 20, 2026, 1:03 p.m.