Triple
T22094488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaane Bhi Do Yaaro |
E545989
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Deepak Qazir |
—
|
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: Deepak Qazir | Statement: [Jaane Bhi Do Yaaro, castMember, Deepak Qazir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deepak Qazir Context triple: [Jaane Bhi Do Yaaro, castMember, Deepak Qazir]
-
A.
Deepak Qazir
chosen
Deepak Qazir is an Indian actor known for his role in the cult television film "In Which Annie Gives It Those Ones."
-
B.
Deepak Tijori
Deepak Tijori is an Indian actor and filmmaker best known for his supporting roles in popular 1990s Bollywood films.
-
C.
Deepak Wirkud
Deepak Wirkud is an editor known for his work on the film "Border."
-
D.
Deepak Nayyar
Deepak Nayyar is an Indian economist and academic known for his work on development economics and his leadership roles in major universities and international economic institutions.
-
E.
Ashutosh Rana
Ashutosh Rana is an acclaimed Indian film and television actor known for his intense character roles and powerful villainous performances in Hindi and regional cinema.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e766388190aad1039fe0849771 |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.