Triple
T22102749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saaransh |
E546210
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Anupam Kher |
—
|
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: Anupam Kher | Statement: [Saaransh, starring, Anupam Kher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anupam Kher Context triple: [Saaransh, starring, Anupam Kher]
-
A.
Anupam Kher
chosen
Anupam Kher is an acclaimed Indian actor known for his extensive work in Hindi cinema and notable roles in international films.
-
B.
Anil Kapoor
Anil Kapoor is a veteran Indian actor and producer known for his work in Hindi cinema and international films, recognized for his energetic screen presence and roles in movies like "Mr. India," "Dil Dhadakne Do," and the series "24."
-
C.
Sanjeev Bhaskar
Sanjeev Bhaskar is a British comedian, actor, and writer best known for his work on the sketch show "Goodness Gracious Me" and the sitcom "The Kumars at No. 42."
-
D.
Anupam Tripathi
Anupam Tripathi is an Indian actor best known internationally for his breakout role as Ali Abdul in the South Korean Netflix series "Squid Game."
-
E.
Gulshan Grover
Gulshan Grover is an Indian film actor, popularly known as Bollywood’s “Bad Man” for his numerous villainous roles across Hindi 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129175a7881909549883f23c53dca |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.