Triple
T21945309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farah Naaz |
E541917
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Mithun Chakraborty |
—
|
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: Mithun Chakraborty | Statement: [Farah Naaz, workedWith, Mithun Chakraborty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mithun Chakraborty Context triple: [Farah Naaz, workedWith, Mithun Chakraborty]
-
A.
Mithun Chakraborty
chosen
Mithun Chakraborty is a renowned Indian actor and former Bollywood superstar known for his versatile performances across Hindi and Bengali cinema, as well as his iconic dancing style.
-
B.
Bablu Chakraborty
Bablu Chakraborty is a music composer known for his work on the Hindi film "Dil Vil Pyar Vyar."
-
C.
Srijit Mukherji
Srijit Mukherji is an acclaimed Indian filmmaker and screenwriter known for his influential and genre-diverse work in contemporary Bengali cinema.
-
D.
Krishna Mukherjee
Krishna Mukherjee is the mother of acclaimed Indian film actress Rani Mukerji and a member of the prominent Mukherjee-Samarth family in Bollywood.
-
E.
Shekhar Chatterjee
Shekhar Chatterjee was an Indian actor known for his work in Bengali cinema and theatre.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12427c2b48190949c41bd3be2d9f3 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.