Triple
T21428321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudaali |
E528618
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Raj Babbar |
—
|
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: Raj Babbar | Statement: [Rudaali, starring, Raj Babbar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raj Babbar Context triple: [Rudaali, starring, Raj Babbar]
-
A.
Raj Babbar
chosen
Raj Babbar is an Indian film and television actor turned politician, known for his work in Hindi and Punjabi cinema and his long-standing association with the Indian National Congress.
-
B.
Ravi Nandan
Ravi Nandan is a television and film producer known for his executive production work on comedy series such as "Playing House."
-
C.
Robin Bhatt
Robin Bhatt is an Indian screenwriter known for his work on numerous successful Bollywood films, particularly in the romance and drama genres.
-
D.
Vinod Khanna
Vinod Khanna was a prominent Indian film actor and politician, known for his leading roles in Hindi cinema from the 1970s onward and later service as a Member of Parliament.
-
E.
Raj Kamal
Raj Kamal is a character in the Indian film "Rangeela," around whom part of the movie’s romantic and dramatic narrative revolves.
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b3e74bcc81909ad66e3c59152ffc |
completed | April 22, 2026, 11:41 a.m. |
Created at: April 16, 2026, 5:49 p.m.