Triple
T22111566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buniyaad |
E546429
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Alok Nath |
—
|
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: Alok Nath | Statement: [Buniyaad, starring, Alok Nath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alok Nath Context triple: [Buniyaad, starring, Alok Nath]
-
A.
Alok Nath
chosen
Alok Nath is an Indian film and television actor best known for his frequent portrayals of traditional, patriarchal father figures in Hindi cinema and TV serials.
-
B.
Anand Bakshi
Anand Bakshi was a prolific and celebrated Indian lyricist who wrote songs for hundreds of Hindi films over several decades.
-
C.
Arun Dutt
Arun Dutt is an Indian film personality best known as the son of legendary filmmaker and actor Guru Dutt.
-
D.
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.
-
E.
Kumar Shahani
Kumar Shahani is an Indian filmmaker and theorist known for his pioneering work in the Indian New Wave and his formally experimental, intellectually rigorous 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12949cc7881908898ca7dc130f57f |
completed | April 28, 2026, 9:40 p.m. |
Created at: April 16, 2026, 8:31 p.m.