Triple
T22094469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaane Bhi Do Yaaro |
E545989
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Satish Kaushik |
—
|
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: Satish Kaushik | Statement: [Jaane Bhi Do Yaaro, screenwriter, Satish Kaushik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satish Kaushik Context triple: [Jaane Bhi Do Yaaro, screenwriter, Satish Kaushik]
-
A.
Satish Kaushik
chosen
Satish Kaushik was an Indian actor, director, producer, and screenwriter known for his work in Hindi cinema and theatre, as well as for his memorable comic roles and acclaimed direction.
-
B.
Satish Jain
Satish Jain is an Indian economist and academic known for his contributions to economic theory and his association with the Delhi School of Economics.
-
C.
Ashok Saraf
Ashok Saraf is a veteran Indian actor and comedian best known for his prolific work in Marathi films and theatre, as well as memorable roles in Hindi cinema and television.
-
D.
Vinod Dikshit
Vinod Dikshit was an Indian civil servant and the husband of longtime Delhi Chief Minister Sheila Dikshit.
-
E.
Aravind Joshi
Aravind Joshi was an Indian-American computer scientist and computational linguist known for pioneering work in formal grammar formalisms, particularly Tree Adjoining Grammars, and for foundational contributions to natural language processing.
- 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.