Triple
T22075972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dilip Kumar |
E545521
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Saira Banu |
—
|
NE NERFINISHED |
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: Saira Banu | Statement: [Dilip Kumar, spouse, Saira Banu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saira Banu Context triple: [Dilip Kumar, spouse, Saira Banu]
-
A.
Saira Banu
chosen
Saira Banu is a celebrated Indian film actress best known for her work in Hindi cinema during the 1960s and 1970s and as the wife of legendary actor Dilip Kumar.
-
B.
Sharmila Basu
Sharmila Basu is a relatively obscure individual about whom no widely known public or biographical information is readily available.
-
C.
Smita Patil
Smita Patil was a critically acclaimed Indian actress known for her powerful performances in parallel cinema during the 1970s and 1980s.
-
D.
Asha Parekh
Asha Parekh is a celebrated Indian film actress and former Bollywood star of the 1960s and 1970s, renowned for her versatile performances and significant contributions to Hindi cinema.
-
E.
Dimple Kapadia
Dimple Kapadia is a renowned Indian film actress known for her work in Hindi cinema since the 1970s, acclaimed for both mainstream and critically lauded roles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b2bf60819082d38e671f160b0f |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:28 p.m.