Triple
T22433410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mukti Bhawan |
E554552
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Lalit Behl |
—
|
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: Lalit Behl | Statement: [Mukti Bhawan, starring, Lalit Behl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lalit Behl Context triple: [Mukti Bhawan, starring, Lalit Behl]
-
A.
Lalit Behl
chosen
Lalit Behl was an Indian actor and filmmaker known for his nuanced performances in independent and art-house cinema.
-
B.
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.
-
C.
Suresh Ayyar
Suresh Ayyar is an editor known for his work on the acclaimed Australian memoir "Romulus, My Father."
-
D.
Brij Mohan
Brij Mohan is the given name of B. M. Kaul, an individual identifiable by the initials B.M. Kaul.
-
E.
Lalit Parimoo
Lalit Parimoo is an Indian film and television actor best known for his character roles in Hindi cinema and TV, including his notable performance in the superhero series "Shaktimaan."
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15adce9688190992ad0ca15883931 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 16, 2026, 8:47 p.m.